1,422,860 results on '"Choi, So"'
Search Results
2. Convergence result for the gradient-push algorithm and its application to boost up the Push-DIging algorithm
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Choi, Hyogi, Choi, Woocheol, and Kim, Gwangil
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Mathematics - Optimization and Control ,Electrical Engineering and Systems Science - Systems and Control - Abstract
The gradient-push algorithm is a fundamental algorithm for the distributed optimization problem \begin{equation} \min_{x \in \mathbb{R}^d} f(x) = \sum_{j=1}^n f_j (x), \end{equation} where each local cost $f_j$ is only known to agent $a_i$ for $1 \leq i \leq n$ and the agents are connected by a directed graph. In this paper, we obtain convergence results for the gradient-push algorithm with constant stepsize whose range is sharp in terms the order of the smoothness constant $L>0$. Precisely, under the two settings: 1) Each local cost $f_i$ is strongly convex and $L$-smooth, 2) Each local cost $f_i$ is convex quadratic and $L$-smooth while the aggregate cost $f$ is strongly convex, we show that the gradient-push algorithm with stepsize $\alpha>0$ converges to an $O(\alpha)$-neighborhood of the minimizer of $f$ for a range $\alpha \in (0, c/L]$ with a value $c>0$ independent of $L>0$. As a benefit of the result, we suggest a hybrid algorithm that performs the gradient-push algorithm with a relatively large stepsize $\alpha>0$ for a number of iterations and then go over to perform the Push-DIGing algorithm. It is verified by a numerical test that the hybrid algorithm enhances the performance of the Push-DIGing algorithm significantly. The convergence results of the gradient-push algorithm are also supported by numerical tests.
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- 2024
3. Mask2Map: Vectorized HD Map Construction Using Bird's Eye View Segmentation Masks
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Choi, Sehwan, Kim, Jungho, Shin, Hongjae, and Choi, Jun Won
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Computer Science - Computer Vision and Pattern Recognition - Abstract
In this paper, we introduce Mask2Map, a novel end-to-end online HD map construction method designed for autonomous driving applications. Our approach focuses on predicting the class and ordered point set of map instances within a scene, represented in the bird's eye view (BEV). Mask2Map consists of two primary components: the Instance-Level Mask Prediction Network (IMPNet) and the Mask-Driven Map Prediction Network (MMPNet). IMPNet generates Mask-Aware Queries and BEV Segmentation Masks to capture comprehensive semantic information globally. Subsequently, MMPNet enhances these query features using local contextual information through two submodules: the Positional Query Generator (PQG) and the Geometric Feature Extractor (GFE). PQG extracts instance-level positional queries by embedding BEV positional information into Mask-Aware Queries, while GFE utilizes BEV Segmentation Masks to generate point-level geometric features. However, we observed limited performance in Mask2Map due to inter-network inconsistency stemming from different predictions to Ground Truth (GT) matching between IMPNet and MMPNet. To tackle this challenge, we propose the Inter-network Denoising Training method, which guides the model to denoise the output affected by both noisy GT queries and perturbed GT Segmentation Masks. Our evaluation conducted on nuScenes and Argoverse2 benchmarks demonstrates that Mask2Map achieves remarkable performance improvements over previous state-of-the-art methods, with gains of 10.1% mAP and 4.1 mAP, respectively. Our code can be found at https://github.com/SehwanChoi0307/Mask2Map., Comment: 20 pages, 9 figures
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- 2024
4. Centrality dependence of L\'evy-stable two-pion Bose-Einstein correlations in $\sqrt{s_{_{NN}}}=200$ GeV Au$+$Au collisions
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PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Aidala, C., Ajitanand, N. N., Akiba, Y., Akimoto, R., Al-Ta'ani, H., Alexander, J., Angerami, A., Aoki, K., Apadula, N., Aramaki, Y., Asano, H., Aschenauer, E. C., Atomssa, E. T., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Bannier, B., Barish, K. N., Bassalleck, B., Bathe, S., Baublis, V., Baumgart, S., Bazilevsky, A., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Buesching, H., Bumazhnov, V., Butsyk, S., Campbell, S., Castera, P., Chen, C. -H., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choi, S., Choudhury, R. K., Christiansen, P., Chujo, T., Chvala, O., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Corliss, R., Csanád, M., Csörgő, T., D'Orazio, L., Dairaku, S., Datta, A., Daugherity, M. S., David, G., Denisov, A., Deshpande, A., Desmond, E. J., Dharmawardane, K. V., Dietzsch, O., Ding, L., Dion, A., Donadelli, M., Doomra, V., Drapier, O., Drees, A., Drees, K. A., Durham, J. M., Durum, A., Edwards, S., Efremenko, Y. V., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukao, Y., Fusayasu, T., Gainey, K., Gal, C., Garishvili, A., Garishvili, I., Glenn, A., Gong, X., Gonin, M., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, L., Guo, T., Gustafsson, H. -Å., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hanks, J., Hashimoto, K., Haslum, E., Hayano, R., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Horaguchi, T., Hori, Y., Ichihara, T., Iinuma, H., Ikeda, Y., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Issah, M., Ivanishchev, D., Jacak, B. V., Javani, M., Jiang, X., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kamin, J., Kaneti, S., Kang, B. H., Kang, J. H., Kang, J. S., Kapustinsky, J., Karatsu, K., Kasai, M., Kasza, G., Kawall, D., Kazantsev, A. V., Kempel, T., Khanzadeev, A., Kijima, K. M., Kim, B. I., Kim, C., Kim, D. J., Kim, E. -J., Kim, H. J., Kim, K. -B., Kim, Y. -J., Kim, Y. K., Kinney, E., Kiss, Á., Kistenev, E., Klatsky, J., Kleinjan, D., Kline, P., Komatsu, Y., Komkov, B., Koster, J., Kotchetkov, D., Kotov, D., Kovacs, L., Krizek, F., Král, A., Kunde, G. J., Kurgyis, B., Kurita, K., Kurosawa, M., Kwon, Y., Kyle, G. S., Lai, Y. S., Lajoie, J. G., Lebedev, A., Lee, B., Lee, D. M., Lee, J., Lee, K. B., Lee, K. S., Lee, S. H., Lee, S. R., Leitch, M. J., Leite, M. A. L., Leitgab, M., Lewis, B., Lim, S. H., Levy, L. A. Linden, Liu, M. X., Lökös, S., Loomis, D. A., Love, B., Maguire, C. F., Makdisi, Y. I., Makek, M., Manion, A., Manko, V. I., Mannel, E., Masumoto, S., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Mendoza, M., Meredith, B., Miake, Y., Mibe, T., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Miyachi, Y., Miyasaka, S., Mohanty, A. K., Mohapatra, S., Moon, H. J., Morrison, D. P., Motschwiller, S., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagae, T., Nagamiya, S., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakamiya, Y., Nakamura, K. R., Nakamura, T., Nakano, K., Nattrass, C., Nederlof, A., Nihashi, M., Nouicer, R., Novák, T., Novitzky, N., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Okada, K., Orosz, M., Oskarsson, A., Ouchida, M., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, B. H., Park, I. H., Park, J. S., Park, S., Park, S. K., Patel, L., Pate, S. F., Pei, H., Peng, J. -C., Pereira, H., Peressounko, D. Yu., Petti, R., Pinkenburg, C., Pisani, R. P., Potekhin, M., Proissl, M., Purschke, M. L., Qu, H., Rak, J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richardson, E., Richford, D., Roach, D., Roche, G., Rolnick, S. D., Rosati, M., Sahlmueller, B., Saito, N., Sakaguchi, T., Samsonov, V., Sano, M., Sarsour, M., Sawada, S., Sedgwick, K., Seidl, R., Sen, A., Seto, R., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Sim, K. S., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Sugitate, T., Sukhanov, A., Sun, J., Sun, Z., Sziklai, J., Takagui, E. M., Takahara, A., Taketani, A., Tanaka, Y., Taneja, S., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tennant, E., Themann, H., Todoroki, T., Tomášek, L., Tomášek, M., Torii, H., Towell, R. S., Tserruya, I., Tsuchimoto, Y., Tsuji, T., Ujvari, B., Vale, C., van Hecke, H. W., Vargyas, M., Vazquez-Zambrano, E., Veicht, A., Velkovska, J., Virius, M., Vossen, A., Vrba, V., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, D., Watanabe, K., Watanabe, Y., Watanabe, Y. S., Wei, F., Wei, R., White, S. N., Winter, D., Wolin, S., Woody, C. L., Wysocki, M., Xia, B., Yamaguchi, Y. L., Yang, R., Yanovich, A., Ying, J., Yokkaichi, S., Younus, I., You, Z., Yushmanov, I. E., Zajc, W. A., and Zelenski, A.
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Nuclear Experiment - Abstract
The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
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- 2024
5. Feature Diversification and Adaptation for Federated Domain Generalization
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Yang, Seunghan, Choi, Seokeon, Park, Hyunsin, Choi, Sungha, Chang, Simyung, and Yun, Sungrack
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Computer Science - Machine Learning ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Federated learning, a distributed learning paradigm, utilizes multiple clients to build a robust global model. In real-world applications, local clients often operate within their limited domains, leading to a `domain shift' across clients. Privacy concerns limit each client's learning to its own domain data, which increase the risk of overfitting. Moreover, the process of aggregating models trained on own limited domain can be potentially lead to a significant degradation in the global model performance. To deal with these challenges, we introduce the concept of federated feature diversification. Each client diversifies the own limited domain data by leveraging global feature statistics, i.e., the aggregated average statistics over all participating clients, shared through the global model's parameters. This data diversification helps local models to learn client-invariant representations while preserving privacy. Our resultant global model shows robust performance on unseen test domain data. To enhance performance further, we develop an instance-adaptive inference approach tailored for test domain data. Our proposed instance feature adapter dynamically adjusts feature statistics to align with the test input, thereby reducing the domain gap between the test and training domains. We show that our method achieves state-of-the-art performance on several domain generalization benchmarks within a federated learning setting., Comment: Accepted to ECCV 2024
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- 2024
6. Evidence of $h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta$ decay and search for $h_{b}(\text{1P,2P}) \to \Upsilon(\text{1S})\pi^0$ with the Belle detector
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Belle Collaboration, Kovalenko, E., Adachi, I., Aihara, H., Asner, D. M., Aushev, T., Ayad, R., Babu, V., Banerjee, Sw., Belous, K., Bennett, J., Bessner, M., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bondar, A., Bozek, A., Bračko, M., Branchini, P., Browder, T. E., Budano, A., Campajola, M., Chang, M. -C., Cheon, B. G., Chilikin, K., Cho, H. E., Cho, K., Cho, S. -J., Choi, S. -K., Choi, Y., Choudhury, S., Dash, N., De Nardo, G., De Pietro, G., Dhamija, R., Di Capua, F., Doležal, Z., Dong, T. V., Dubey, S., Ecker, P., Epifanov, D., Ferlewicz, D., Fulsom, B. G., Garg, R., Gaur, V., Garmash, A., Giri, A., Goldenzweig, P., Graziani, E., Gu, T., Guan, Y., Gudkova, K., Hadjivasiliou, C., Hara, T., Hayasaka, K., Hazra, S., Hou, W. -S., Hsu, C. -L., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobs, W. W., Jin, Y., Kawasaki, T., Kiesling, C., Kim, C. H., Kim, D. Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Korobov, A., Korpar, S., Križan, P., Krokovny, P., Kuhr, T., Kumar, R., Kumara, K., Kuzmin, A., Kwon, Y. -J., Lai, Y. -T., Lam, T., Levit, D., Li, L. K., Gioi, L. Li, Libby, J., Liventsev, D., Ma, Y., Martini, A., Masuda, M., Matsuda, T., Matvienko, D., Meier, F., Merola, M., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Mussa, R., Nakamura, I., Nakao, M., Natkaniec, Z., Natochii, A., Nayak, L., Nayak, M., Niiyama, M., Nishida, S., Ogawa, S., Ono, H., Pakhlova, G., Pardi, S., Park, J., Park, S. -H., Passeri, A., Patra, S., Paul, S., Pedlar, T. K., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Purohit, M. V., Rout, N., Russo, G., Sandilya, S., Santelj, L., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Sevior, M. E., Shan, W., Sharma, C., Shiu, J. -G., Shwartz, B., Sokolov, A., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Tiwary, R., Uchida, M., Unno, Y., Uno, S., Usov, Y., Vinokurova, A., Wang, D., Wang, E., Wang, M. -Z., Wang, X. L., Won, E., Yabsley, B. D., Yan, W., Yang, S. B., Yelton, J., Yin, J. H., Yook, Y., Yuan, C. Z., Zhang, Z. P., and Zhilich, V.
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High Energy Physics - Experiment - Abstract
We report the first evidence for the $h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta$ transition with a significance of $3.5$ standard deviations. The decay branching fraction is measured to be $\mathcal{B}[h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta]=(7.1 ~^{+3.7} _{-3.2}\pm 0.8)\times10^{-3}$, which is noticeably smaller than expected. We also set upper limits on $\pi^0$ transitions of $\mathcal{B}[h_{b}(\text{2P}) \to \Upsilon(\text{1S})\pi^0] < 1.8\times10^{-3}$, and $\mathcal{B}[h_{b}(\text{1P})\to \Upsilon(\text{1S})\pi^0] < 1.8\times10^{-3}$, at the $90\%$ confidence level. These results are obtained with a $131.4$~fb$^{-1}$ data sample collected near the $\Upsilon(\text{5S})$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+e^-$ collider., Comment: to be submitted to PRL
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- 2024
7. Study of $\chi_{bJ}(2P)\to\omega\Upsilon(1S)$ at Belle
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Belle Collaboration, Stottler, Z. S., Pedlar, T. K., Fulsom, B. G., Adachi, I., Adamczyk, K., Aihara, H., Said, S. Al, Asner, D. M., Atmacan, H., Aushev, T., Ayad, R., Babu, V., Banerjee, Sw., Bauer, M., Behera, P., Belous, K., Bennett, J., Bernlochner, F., Bessner, M., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bonvicini, G., Borah, J., Bozek, A., Branchini, P., Browder, T. E., Budano, A., Campajola, M., Cao, L., Červenkov, D., Chang, M. -C., Cheon, B. G., Chilikin, K., Cho, H. E., Cho, K., Choi, S. -K., Choi, Y., Choudhury, S., Cinabro, D., Das, S., De Nardo, G., De Pietro, G., Dhamija, R., Di Capua, F., Doležal, Z., Dong, T. V., Dubey, S., Ecker, P., Epifanov, D., Ferber, T., Ferlewicz, D., Gaur, V., Garmash, A., Giri, A., Goldenzweig, P., Graziani, E., Gu, T., Guan, Y., Gudkova, K., Hadjivasiliou, C., Hara, T., Hayasaka, K., Hazra, S., Hedges, M. T., Herrmann, D., Hou, W. -S., Hsu, C. -L., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Iwasaki, Y., Jacobs, W. W., Jia, S., Jin, Y., Kaliyar, A. B., Kawasaki, T., Kiesling, C., Kim, C. H., Kim, D. Y., Kim, K. -H., Kim, Y. -K., Kodyš, P., Korobov, A., Korpar, S., Kovalenko, E., Križan, P., Krokovny, P., Kuhr, T., Kumar, M., Kumar, R., Kumara, K., Kuzmin, A., Kwon, Y. -J., Lai, Y. -T., Lam, T., Laurenza, M., Lee, S. C., Levit, D., Lewis, P., Li, L. K., Libby, J., Lieret, K., Liventsev, D., Luo, T., Ma, Y., Masuda, M., Maurya, S. K., Meier, F., Merola, M., Miyabayashi, K., Mohanty, G. B., Nakamura, I., Nakao, M., Natochii, A., Nayak, L., Nisar, N. K., Nishida, S., Ogawa, K., Ogawa, S., Ono, H., Oskin, P., Pakhlov, P., Pakhlova, G., Pang, T., Pardi, S., Park, J., Park, S. -H., Patra, S., Paul, S., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Rout, N., Russo, G., Sandilya, S., Sangal, A., Santelj, L., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Shan, W., Shapkin, M., Sharma, C., Shiu, J. -G., Sokolov, A., Solovieva, E., Starič, M., Sumihama, M., Sutcliffe, W., Takizawa, M., Tanida, K., Tenchini, F., Tiwary, R., Uchida, M., Unno, Y., Uno, S., Vahsen, S. E., Varner, G., Wang, D., Wang, E., Wang, M. -Z., Watanuki, S., Werbycka, O., Won, E., Yabsley, B. D., Yan, W., Yin, J. H., Yuan, C. Z., Yuan, L., Yusa, Y., Zhang, Z. P., Zhilich, V., and Zhukova, V.
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High Energy Physics - Experiment - Abstract
We report a study of the hadronic transitions $\chi_{bJ}(2P)\to\omega\Upsilon(1S)$, with $\omega\to\pi^{+}\pi^{-}\pi^{0}$, using $28.2\times10^6~\Upsilon(3S)$ mesons recorded by the Belle detector. We present the first evidence for the near--threshold transition $\chi_{b0}(2P)\to\omega\Upsilon(1S)$, the analog of the charm sector decay $\chi_{c1}(3872)\to\omega J/\psi$, with a branching fraction of $B\big(\chi_{b0}(2P)\to\omega\Upsilon(1S)\big) = \big(0.55\pm0.19\pm0.07\big)\%$. We also obtain branching fractions of $B\big(\chi_{b1}(2P)\to\omega\Upsilon(1S)\big) = \big(2.39{}^{+0.20}_{-0.19}\pm0.24\big)\%$ and $B\big(\chi_{b2}(2P)\to\omega\Upsilon(1S)\big) = \big(0.47{}^{+0.13}_{-0.12}\pm0.06\big)\%$, confirming the measurement of the $\omega$ transitions of the $J=1,2~P$--wave states. The ratio for the $J=2$ to $J=1$ transitions is also measured and found to differ by 3.3 standard deviations from the expected value in the QCD multipole expansion., Comment: 6 pages, 2 figures
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- 2024
8. CLOi-Mapper: Consistent, Lightweight, Robust, and Incremental Mapper With Embedded Systems for Commercial Robot Services
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Noh, DongKi, Lim, Hyungtae, Eoh, Gyuho, Choi, Duckyu, Choi, Jeongsik, Lim, Hyunjun, Baek, SeungMin, and Myung, Hyun
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Computer Science - Robotics - Abstract
In commercial autonomous service robots with several form factors, simultaneous localization and mapping (SLAM) is an essential technology for providing proper services such as cleaning and guidance. Such robots require SLAM algorithms suitable for specific applications and environments. Hence, several SLAM frameworks have been proposed to address various requirements in the past decade. However, we have encountered challenges in implementing recent innovative frameworks when handling service robots with low-end processors and insufficient sensor data, such as low-resolution 2D LiDAR sensors. Specifically, regarding commercial robots, consistent performance in different hardware configurations and environments is more crucial than the performance dedicated to specific sensors or environments. Therefore, we propose a) a multi-stage %hierarchical approach for global pose estimation in embedded systems; b) a graph generation method with zero constraints for synchronized sensors; and c) a robust and memory-efficient method for long-term pose-graph optimization. As verified in in-home and large-scale indoor environments, the proposed method yields consistent global pose estimation for services in commercial fields. Furthermore, the proposed method exhibits potential commercial viability considering the consistent performance verified via mass production and long-term (> 5 years) operation.
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- 2024
9. Search for charmed baryons in the $\Lambda_c^+\eta$ system and measurement of the branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $\Lambda_c^+\eta$ and $pD^0$ relative to $\Sigma_c(2455)\pi$
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Belle Collaboration, Li, S. X., Shen, C. P., Adachi, I., Ahn, J. K., Aihara, H., Asner, D. M., Atmacan, H., Aushev, T., Ayad, R., Banerjee, Sw., Belous, K., Bennett, J., Bessner, M., Bilka, T., Biswas, D., Bodrov, D., Bozek, A., Bračko, M., Branchini, P., Browder, T. E., Budano, A., Campajola, M., Chang, M. -C., Cheon, B. G., Chilikin, K., Cho, H. E., Cho, K., Choi, S. -K., Choi, Y., Choudhury, S., Dash, N., De Nardo, G., De Pietro, G., Dhamija, R., Dingfelder, J., Doležal, Z., Dong, T. V., Dubey, S., Ecker, P., Ferber, T., Fulsom, B. G., Gaur, V., Garmash, A., Goldenzweig, P., Graziani, E., Grube, B., Guan, Y., Gudkova, K., Hadjivasiliou, C., Hsu, C. -L., Ipsita, N., Itoh, R., Iwasaki, M., Jacobs, W. W., Ji, Q. P., Jia, S., Jin, Y., Joo, K. K., Kiesling, C., Kim, D. Y., Kim, Y. J., Kinoshita, K., Kodyš, P., Korobov, A., Korpar, S., Kovalenko, E., Križan, P., Krokovny, P., Kuhr, T., Kumar, R., Kumara, K., Kwon, Y. -J., Li, L. K., Li, Y., Li, Y. B., Liventsev, D., Masuda, M., Maurya, S. K., Meier, F., Merola, M., Miyabayashi, K., Mizuk, R., Mussa, R., Nakano, T., Nakao, M., Natochii, A., Nayak, M., Nishida, S., Pakhlov, P., Pakhlova, G., Pardi, S., Park, J., Park, S. -H., Patra, S., Paul, S., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Russo, G., Sandilya, S., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Shiu, J. -G., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Uchida, M., Uglov, T., Uno, S., Wang, E., Won, E., Yabsley, B. D., Yan, W., Yelton, J., Yin, J. H., Yuan, L., and Zhilich, V.
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High Energy Physics - Experiment ,High Energy Physics - Phenomenology - Abstract
We search for excited charmed baryons in the $\Lambda_c^+\eta$ system using a data sample corresponding to an integrated luminosity of 980 $\rm fb^{-1}$. The data were collected by the Belle detector at the KEKB $e^{+}$$e^{-}$ asymmetric-energy collider. No significant signals are found in the $\Lambda_c^+\eta$ mass spectrum, including the known $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$. Clear $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ signals are observed in the $pD^0$ mass spectrum. We set upper limits at 90\% credibility level on ratios of branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $\Lambda_c^+\eta$ relative to $\Sigma_c(2455)\pi$ of $<0.13$ for the $\Lambda_c(2880)^+$ and $<1.11$ for the $\Lambda_c(2940)^+$. We measure ratios of branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $pD^0$ relative to $\Sigma_c(2455)\pi$ of $0.75 \pm 0.03(\text{stat.}) \pm 0.07(\text{syst.})$ for the $\Lambda_c(2880)^+$ and $3.59 \pm 0.21(\text{stat.}) \pm 0.56(\text{syst.})$ for the $\Lambda_c(2940)^+$., Comment: 10 pages, 4 figures
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- 2024
10. Self Training and Ensembling Frequency Dependent Networks with Coarse Prediction Pooling and Sound Event Bounding Boxes
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Nam, Hyeonuk, Min, Deokki, Choi, Seungdeok, Choi, Inhan, and Park, Yong-Hwa
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Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Sound - Abstract
To tackle sound event detection (SED) task, we propose frequency dependent networks (FreDNets), which heavily leverage frequency-dependent methods. We apply frequency warping and FilterAugment, which are frequency-dependent data augmentation methods. The model architecture consists of 3 branches: audio teacher-student transformer (ATST) branch, BEATs branch and CNN branch including either partial dilated frequency dynamic convolution (PDFD) or squeeze-and-Excitation (SE) with time-frame frequency-wise SE (tfwSE). To train MAESTRO labels with coarse temporal resolution, we apply max pooling on prediction for the MAESTRO dataset. Using best ensemble model, we apply self training to obtain pseudo label from DESED weak set, DESED unlabeled set and AudioSet. AudioSet labels are filtered to focus on high-confidence pseudo labels and AudioSet pseudo labels are used to train on DESED labels only. We used change-detection-based sound event bounding boxes (cSEBBs) as post processing for ensemble models on self training and submission models., Comment: DCASE 2024 Challenge Task 4 technical report
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- 2024
11. DataFreeShield: Defending Adversarial Attacks without Training Data
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Lee, Hyeyoon, Choi, Kanghyun, Kwon, Dain, Park, Sunjong, Jaiswal, Mayoore Selvarasa, Park, Noseong, Choi, Jonghyun, and Lee, Jinho
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Recent advances in adversarial robustness rely on an abundant set of training data, where using external or additional datasets has become a common setting. However, in real life, the training data is often kept private for security and privacy issues, while only the pretrained weight is available to the public. In such scenarios, existing methods that assume accessibility to the original data become inapplicable. Thus we investigate the pivotal problem of data-free adversarial robustness, where we try to achieve adversarial robustness without accessing any real data. Through a preliminary study, we highlight the severity of the problem by showing that robustness without the original dataset is difficult to achieve, even with similar domain datasets. To address this issue, we propose DataFreeShield, which tackles the problem from two perspectives: surrogate dataset generation and adversarial training using the generated data. Through extensive validation, we show that DataFreeShield outperforms baselines, demonstrating that the proposed method sets the first entirely data-free solution for the adversarial robustness problem., Comment: ICML 2024
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- 2024
12. i-SRT: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective Judgment
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Ahn, Daechul, Choi, Yura, Kim, San, Yu, Youngjae, Kang, Dongyeop, and Choi, Jonghyun
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Aligning Video Large Multimodal Models (VLMMs) face challenges such as modality misalignment and verbose responses. Although iterative approaches such as self-rewarding or iterative direct preference optimization (DPO) recently showed a significant improvement in language model alignment, particularly on reasoning tasks, self-aligned models applied to large video-language models often result in lengthy and irrelevant responses. To address these challenges, we propose a novel method that employs self-retrospection to enhance both response generation and preference modeling, and call iterative self-retrospective judgment (i-SRT). By revisiting and evaluating already generated content and preference in loop, i-SRT improves the alignment between textual and visual modalities, reduce verbosity, and enhances content relevance. Our empirical evaluations across diverse video question answering benchmarks demonstrate that i-SRT significantly outperforms prior arts. We are committed to opensourcing our code, models, and datasets to encourage further investigation., Comment: Technical report
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- 2024
13. Jet modification via $\pi^0$-hadron correlations in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV
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PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Afanasiev, S., Aidala, C., Ajitanand, N. N., Akiba, Y., Al-Bataineh, H., Alexander, J., Alfred, M., Aoki, K., Apadula, N., Aphecetche, L., Asai, J., Asano, H., Atomssa, E. T., Averbeck, R., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Baksay, G., Baksay, L., Baldisseri, A., Bandara, N. S., Bannier, B., Barish, K. N., Barnes, P. D., Bassalleck, B., Basye, A. T., Bathe, S., Batsouli, S., Baublis, V., Baumann, C., Bazilevsky, A., Beaumier, M., Beckman, S., Belikov, S., Belmont, R., Bennett, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Bickley, A. A., Blankenship, B., Blau, D. S., Boissevain, J. G., Bok, J. S., Borel, H., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Buesching, H., Bumazhnov, V., Bunce, G., Butsyk, S., Camacho, C. M., Campbell, S., Chang, B. S., Chang, W. C., Charvet, J. L., Chen, C. -H., Chen, D., Chernichenko, S., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choudhury, R. K., Chujo, T., Chung, P., Churyn, A., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Constantin, P., Corliss, R., Csanád, M., Csörgő, T., d'Enterria, D., Dahms, T., Dairaku, S., Danley, T. W., Das, K., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dietzsch, O., Dion, A., Diss, P. B., Donadelli, M., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Dubey, A. K., Durham, J. M., Durum, A., Dutta, D., Dzhordzhadze, V., Efremenko, Y. V., Ellinghaus, F., En'yo, H., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Fraenkel, Z., Frantz, J. E., Franz, A., Frawley, A. D., Fujiwara, K., Fukao, Y., Fusayasu, T., Gallus, P., Gal, C., Garg, P., Garishvili, I., Ge, H., Giordano, F., Glenn, A., Gong, H., Gonin, M., Gosset, J., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Gustafsson, H. -Å., Hachiya, T., Henni, A. Hadj, Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, R., Han, S. Y., Hartouni, E. P., Haruna, K., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Haslum, E., Hayano, R., Heffner, M., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hodges, A., Hohlmann, M., Hollis, R. S., Holzmann, W., Homma, K., Hong, B., Horaguchi, T., Hornback, D., Hoshino, T., Hotvedt, N., Huang, J., Ichihara, T., Ichimiya, R., Iinuma, H., Ikeda, Y., Imai, K., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Ishihara, M., Isobe, T., Issah, M., Isupov, A., Ivanishchev, D., Jacak, B. V., Jezghani, M., Jiang, X., Jin, J., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kajihara, F., Kametani, S., Kamihara, N., Kamin, J., Kanda, S., Kang, J. H., Kapustinsky, J., Kawall, D., Kazantsev, A. V., Kempel, T., Key, J. A., Khachatryan, V., Khanzadeev, A., Kijima, K. M., Kikuchi, J., Kimelman, B., Kim, B. I., Kim, C., Kim, D. H., Kim, D. J., Kim, E., Kim, E. -J., Kim, G. W., Kim, M., Kim, S. H., Kinney, E., Kiriluk, K., Kiss, Á., Kistenev, E., Kitamura, R., Klatsky, J., Klay, J., Klein-Boesing, C., Kleinjan, D., Kline, P., Koblesky, T., Kochenda, L., Komkov, B., Konno, M., Koster, J., Kotov, D., Kovacs, L., Kozlov, A., Kravitz, A., Král, A., Kunde, G. J., Kurgyis, B., Kurita, K., Kurosawa, M., Kweon, M. J., Kwon, Y., Kyle, G. S., Lai, Y. S., Lajoie, J. G., Layton, D., Lebedev, A., Lee, D. M., Lee, K. B., Lee, S., Lee, S. H., Lee, T., Leitch, M. J., Leite, M. A. L., Lenzi, B., Liebing, P., Lim, S. H., Litvinenko, A., Liu, H., Liu, M. X., Liška, T., Li, X., Lokos, S., Loomis, D. A., Love, B., Lynch, D., Maguire, C. F., Makdisi, Y. I., Makek, M., Malakhov, A., Malik, M. D., Manion, A., Manko, V. I., Mannel, E., Mao, Y., Masui, H., Matathias, F., Mašek, L., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Means, N., Meles, A., Mendoza, M., Meredith, B., Miake, Y., Mignerey, A. C., Mikeš, P., Miki, K., Milov, A., Mishra, D. K., Mishra, M., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Miyasaka, S., Mizuno, S., Mohanty, A. K., Montuenga, P., Moon, T., Morino, Y., Morreale, A., Morrison, D. P., Moukhanova, T. V., Mukhopadhyay, D., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagamiya, S., Nagashima, K., Nagle, J. L., Naglis, M., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakamiya, Y., Nakamura, T., Nakano, K., Nattrass, C., Netrakanti, P. K., Newby, J., Nguyen, M., Niida, T., Nishimura, S., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Oda, S. X., Ogilvie, C. A., Okada, K., Oka, M., Onuki, Y., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ouchida, M., Ozawa, K., Pak, R., Palounek, A. P. T., Pantuev, V., Papavassiliou, V., Park, J., Park, J. S., Park, S., Park, W. J., Patel, M., Pate, S. F., Pei, H., Peng, J. -C., Pereira, H., Perepelitsa, D. V., Perera, G. D. N., Peresedov, V., Peressounko, D. Yu., Perry, J., Petti, R., Pinkenburg, C., Pinson, R., Pisani, R. P., Potekhin, M., Purschke, M. L., Purwar, A. K., Qu, H., Rakotozafindrabe, A., Rak, J., Ramson, B. J., Ravinovich, I., Read, K. F., Rembeczki, S., Reygers, K., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Roach, D., Roche, G., Rolnick, S. D., Rosati, M., Rosendahl, S. S. E., Rosnet, P., Rowan, Z., Rubin, J. G., Rukoyatkin, P., Ružička, P., Rykov, V. L., Sahlmueller, B., Saito, N., Sakaguchi, T., Sakai, S., Sakashita, K., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sato, T., Sawada, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seele, J., Seidl, R., Semenov, A. Yu., Semenov, V., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Silvestre, C., Sim, K. S., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soldatov, A., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Staley, F., Stankus, P. W., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Sugitate, T., Suire, C., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takagui, E. M., Taketani, A., Tanabe, R., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarján, P., Themann, H., Thomas, T. L., Tieulent, R., Timilsina, A., Todoroki, T., Togawa, M., Toia, A., Tomita, Y., Tomášek, L., Tomášek, M., Torii, H., Towell, C. L., Towell, R., Towell, R. S., Tram, V-N., Tserruya, I., Tsuchimoto, Y., Ujvari, B., Vale, C., Valle, H., van Hecke, H. W., Veicht, A., Velkovska, J., Vinogradov, A. A., Virius, M., Vrba, V., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, Y., Watanabe, Y. S., Wei, F., Wessels, J., White, A. S., White, S. N., Winter, D., Woody, C. L., Wysocki, M., Xia, B., Xie, W., Xue, L., Yalcin, S., Yamaguchi, Y. L., Yamaura, K., Yang, R., Yanovich, A., Ying, J., Yokkaichi, S., Yoon, I., Yoo, J. H., Young, G. R., Younus, I., Yushmanov, I. E., Yu, H., Zajc, W. A., Zaudtke, O., Zelenski, A., Zhang, C., Zhou, S., Zolin, L., and Zou, L.
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Nuclear Experiment - Abstract
High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 534 authors from 83 institutions, 12 pages, 7 figures. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
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- 2024
14. MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature
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Yi, Gyeong Hoon, Choi, Jiwoo, Song, Hyeongyun, Miano, Olivia, Choi, Jaewoong, Bang, Kihoon, Lee, Byungju, Sohn, Seok Su, Buttler, David, Hiszpanski, Anna, Han, Sang Soo, and Kim, Donghun
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Computer Science - Computation and Language - Abstract
Efficiently extracting data from tables in the scientific literature is pivotal for building large-scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule-based extractions are an ineffective approach. To overcome this challenge, we present MaTableGPT, which is a GPT-based table data extractor from the materials science literature. MaTableGPT features key strategies of table data representation and table splitting for better GPT comprehension and filtering hallucinated information through follow-up questions. When applied to a vast volume of water splitting catalysis literature, MaTableGPT achieved an extraction accuracy (total F1 score) of up to 96.8%. Through comprehensive evaluations of the GPT usage cost, labeling cost, and extraction accuracy for the learning methods of zero-shot, few-shot and fine-tuning, we present a Pareto-front mapping where the few-shot learning method was found to be the most balanced solution owing to both its high extraction accuracy (total F1 score>95%) and low cost (GPT usage cost of 5.97 US dollars and labeling cost of 10 I/O paired examples). The statistical analyses conducted on the database generated by MaTableGPT revealed valuable insights into the distribution of the overpotential and elemental utilization across the reported catalysts in the water splitting literature.
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- 2024
15. Improving Multi-lingual Alignment Through Soft Contrastive Learning
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Park, Minsu, Choi, Seyeon, Choi, Chanyeol, Kim, Jun-Seong, and Sohn, Jy-yong
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Computer Science - Computation and Language - Abstract
Making decent multi-lingual sentence representations is critical to achieve high performances in cross-lingual downstream tasks. In this work, we propose a novel method to align multi-lingual embeddings based on the similarity of sentences measured by a pre-trained mono-lingual embedding model. Given translation sentence pairs, we train a multi-lingual model in a way that the similarity between cross-lingual embeddings follows the similarity of sentences measured at the mono-lingual teacher model. Our method can be considered as contrastive learning with soft labels defined as the similarity between sentences. Our experimental results on five languages show that our contrastive loss with soft labels far outperforms conventional contrastive loss with hard labels in various benchmarks for bitext mining tasks and STS tasks. In addition, our method outperforms existing multi-lingual embeddings including LaBSE, for Tatoeba dataset. The code is available at https://github.com/YAI12xLinq-B/IMASCL, Comment: 8 pages, 1 figures, Accepted at NAACL SRW 2024
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- 2024
16. Search for Two-Body $B$ Meson Decays to $\Lambda^{0}$ and $\Omega^{(*)0}_{c}$
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Belle Collaboration, Savinov, V., Adachi, I., Ahn, J. K., Aihara, H., Asner, D. M., Atmacan, H., Ayad, R., Banerjee, Sw., Bennett, J., Bessner, M., Bhardwaj, V., Biswas, D., Bobrov, A., Bodrov, D., Borah, J., Bračko, M., Branchini, P., Browder, T. E., Budano, A., Červenkov, D., Chang, M. -C., Chang, P., Cheon, B. G., Cho, K., Choi, S. -K., Choi, Y., Choudhury, S., Dash, N., De Nardo, G., De Pietro, G., Dhamija, R., Di Capua, F., Dingfelder, J., Doležal, Z., Dubey, S., Ecker, P., Epifanov, D., Ferlewicz, D., Fulsom, B. G., Gaur, V., Giri, A., Goldenzweig, P., Graziani, E., Gu, T., Guan, Y., Gudkova, K., Hadjivasiliou, C., Hayashii, H., Hazra, S., Hedges, M. T., Hou, W. -S., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobs, W. W., Jin, Y., Kalita, D., Kim, C. H., Kim, D. Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Korobov, A., Korpar, S., Kovalenko, E., Križan, P., Krokovny, P., Kuhr, T., Kumar, R., Kumita, T., Kuzmin, A., Kwon, Y. -J., Lai, Y. -T., Lam, T., Lange, J. S., Li, L. K., Li, Y., Li, Y. B., Gioi, L. Li, Libby, J., Liventsev, D., Luo, T., Ma, Y., Masuda, M., Matsuda, T., Maurya, S. K., Meier, F., Merola, M., Nakamura, I., Nakao, M., Natkaniec, Z., Nayak, L., Nayak, M., Nishida, S., Ogawa, S., Ono, H., Pakhlov, P., Pakhlova, G., Pardi, S., Park, H., Park, J., Park, S. -H., Passeri, A., Patra, S., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Russo, G., Sandilya, S., Santelj, L., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Shan, W., Sharma, C., Shiu, J. -G., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Tiwary, R., Trabelsi, K., Uchida, M., Unno, Y., Uno, S., Varvell, K. E., Wang, E., Watanuki, S., Won, E., Xu, X., Yabsley, B. D., Yan, W., Yin, J. H., Yuan, C. Z., Yuan, L., Yusa, Y., Zhang, Z. P., Zhilich, V., and Zhukova, V.
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High Energy Physics - Experiment - Abstract
We report the results of the first search for Standard Model and baryon-number-violating two-body decays of the neutral $B$ mesons to $\Lambda^{0}$ and $\Omega^{(*)0}_c$ using 711~${\rm fb^{-1}}$ of data collected at the $\Upsilon(4S)$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We observe no evidence of signal from any such decays and set 95\% confidence-level upper limits on the products of $B^0$ and $\bar{B}^0$ branching fractions for these two-body decays with $\mathcal{B}(\Omega_{c}^{0} \to \pi^+ \Omega^-)$ in the range between 9.5~$\times 10^{-8}$ and 31.2~$\times 10^{-8}$., Comment: 6 pages, 2 figures, submitted to PRD(L)
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- 2024
17. The daily modulations and broadband strategy in axion searches. An application with CAST-CAPP detector
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Adair, C. M., Altenmüller, K., Anastassopoulos, V., Cuendis, S. Arguedas, Baier, J., Barth, K., Belov, A., Bozicevic, D., Bräuninger, H., Cantatore, G., Caspers, F., Castel, J. F., Çetin, S. A., Chung, W., Choi, H., Choi, J., Dafni, T., Davenport, M., Dermenev, A., Desch, K., Döbrich, B., Fischer, H., Funk, W., Galan, J., Gardikiotis, A., Gninenko, S., Golm, J., Hasinoff, M. D., Hoffmann, D. H. H., Ibáñez, D. Díez, Irastorza, I. G., Jakovčić, K., Kaminski, J., Karuza, M., Krieger, C., Kutlu, Ç., Lakić, B., Laurent, J. M., Lee, J., Lee, S., Luzón, G., Margalejo, C., Maroudas, M., Miceli, L., Mirallas, H., Obis, L., Özbey, A., Özbozduman, K., Pivovaroff, M. J., Rosu, M., Ruz, J., Ruiz-Chóliz, E., Schmidt, S., Semertzidis, Y. K., Solanki, S. K., Stewart, L., Tsagris, I., Vafeiadis, T., Vogel, J. K., Vretenar, M., Youn, S., Zhitnitsky, A., and Zioutas, K.
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High Energy Physics - Experiment ,Astrophysics - Instrumentation and Methods for Astrophysics ,High Energy Physics - Phenomenology ,Physics - Instrumentation and Detectors - Abstract
It has been previously advocated that the presence of the daily and annual modulations of the axion flux on the Earth's surface may dramatically change the strategy of the axion searches. The arguments were based on the so-called Axion Quark Nugget (AQN) dark matter model which was originally put forward to explain the similarity of the dark and visible cosmological matter densities $\Omega_{\rm dark}\sim \Omega_{\rm visible}$. In this framework, the population of galactic axions with mass $ 10^{-6} {\rm eV}\lesssim m_a\lesssim 10^{-3}{\rm eV}$ and velocity $\langle v_a\rangle\sim 10^{-3} c$ will be accompanied by axions with typical velocities $\langle v_a\rangle\sim 0.6 c$ emitted by AQNs. Furthermore, in this framework, it has also been argued that the AQN-induced axion daily modulation (in contrast with the conventional WIMP paradigm) could be as large as $(10-20)\%$, which represents the main motivation for the present investigation. We argue that the daily modulations along with the broadband detection strategy can be very useful tools for the discovery of such relativistic axions. The data from the CAST-CAPP detector have been used following such arguments. Unfortunately, due to the dependence of the amplifier chain on temperature-dependent gain drifts and other factors, we could not conclusively show the presence or absence of a dark sector-originated daily modulation. However, this proof of principle analysis procedure can serve as a reference for future studies., Comment: 18 pages, 8 figures
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- 2024
18. Altermagnetic Polar Metallic phase in Ultra-Thin Epitaxially-Strained RuO2 Films
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Jeong, Seung Gyo, Choi, In Hyeok, Nair, Sreejith, Buiarelli, Luca, Pourbahari, Bita, Oh, Jin Young, Bassim, Nabil, Seo, Ambrose, Choi, Woo Seok, Fernandes, Rafael M., Birol, Turan, Zhao, Liuyan, Lee, Jong Seok, and Jalan, Bharat
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Condensed Matter - Materials Science ,Condensed Matter - Other Condensed Matter - Abstract
Altermagnetism refers to a wide class of compensated magnetic orders featuring magnetic sublattices with opposite spins related by rotational symmetry rather than inversion or translational operations, resulting in non-trivial spin splitting and high-order multipolar orders. Here, by combining theoretical analysis, electrical transport, X-ray and optical spectroscopies, and nonlinear optical measurements, we establish a phase diagram in hybrid molecular beam epitaxy-grown RuO2/TiO2 (110) films, mapping the broken symmetries along the altermagnetic/electronic/structural phase transitions as functions of film thickness and temperature. This phase diagram features a novel altermagnetic metallic polar phase in strained 2 nm samples, extending the concept of multiferroics to altermagnetic systems. These results provide a comprehensive understanding of altermagnetism upon epitaxial heterostructure design for emergent novel phases with multifunctionalities., Comment: 15 pages
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- 2024
19. COPAL: Continual Pruning in Large Language Generative Models
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Malla, Srikanth, Choi, Joon Hee, and Choi, Chiho
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
Adapting pre-trained large language models to different domains in natural language processing requires two key considerations: high computational demands and model's inability to continual adaptation. To simultaneously address both issues, this paper presents COPAL (COntinual Pruning in Adaptive Language settings), an algorithm developed for pruning large language generative models under a continual model adaptation setting. While avoiding resource-heavy finetuning or retraining, our pruning process is guided by the proposed sensitivity analysis. The sensitivity effectively measures model's ability to withstand perturbations introduced by the new dataset and finds model's weights that are relevant for all encountered datasets. As a result, COPAL allows seamless model adaptation to new domains while enhancing the resource efficiency. Our empirical evaluation on a various size of LLMs show that COPAL outperforms baseline models, demonstrating its efficacy in efficiency and adaptability., Comment: ICML2024
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- 2024
20. CookingSense: A Culinary Knowledgebase with Multidisciplinary Assertions
- Author
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Choi, Donghee, Gim, Mogan, Park, Donghyeon, Sung, Mujeen, Kim, Hyunjae, Kang, Jaewoo, and Choi, Jihun
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
This paper introduces CookingSense, a descriptive collection of knowledge assertions in the culinary domain extracted from various sources, including web data, scientific papers, and recipes, from which knowledge covering a broad range of aspects is acquired. CookingSense is constructed through a series of dictionary-based filtering and language model-based semantic filtering techniques, which results in a rich knowledgebase of multidisciplinary food-related assertions. Additionally, we present FoodBench, a novel benchmark to evaluate culinary decision support systems. From evaluations with FoodBench, we empirically prove that CookingSense improves the performance of retrieval augmented language models. We also validate the quality and variety of assertions in CookingSense through qualitative analysis., Comment: LREC-COLING 2024 Accepted
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- 2024
21. First Day at Work
- Author
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Eunho, Jang, Choi, Sophia, and Fulton, Bruce
- Published
- 2021
- Full Text
- View/download PDF
22. U.S. Preservice Teachers Learning with Multilingual Learners in Korea through Educational Technology: Bringing Heteroglossic and Global Approaches to TESOL Teacher Education
- Author
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Ji Hye Shin, Jayoung Choi, Tuba Angay-Crowder, and Nihal Khote
- Abstract
Purpose: This study aimed to explore how educational technology influenced a preparatory teacher education program using heteroglossic and global approaches. Design/Approach/Methods: The researchers drew upon the theoretical framework of multilingual digital storytelling (MDST), which emphasizes the intercultural awareness attributes of multilingual learners (MLs) and takes a heteroglossic perspective in linguistic pedagogy. This qualitative case study examined the experiences of 11 U.S.-based preservice teachers (PSTs) and 12 MLs elementary students in Korea in the MDST project of a TESOL methods course. Findings: The findings showed that PSTs and MLs enhanced their appreciation for educational technology, multilingualism, and intercultural awareness. Although the project aimed to decenter English as a hegemonic language, both PSTs and MLs maintained traditional discourses that privileged English over MLs' home language and targeted literacy correctness in written English only, moving away from the heterogeneous goals of the course project. PSTs and MLs also faced challenges in navigating technological tools, which negatively affected their perception of the project. Originality/Value: This study contributes to heteroglossic approaches in preparatory TESOL teacher education programs and improves the understanding of challenges in educational technology use for global multilingual exchanges to promote global citizenship.
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- 2024
23. The Development and Validation of English Communicative Competence Model for High School Students in Korea
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Whyun Young Choi and Mun-Koo Kang
- Abstract
This study develops and validates an English communicative competence model for Korean high school students, in response to the need to redefine the relevant concepts and components of competence that are demanded by the rapidly evolving future society. Drawing on Celce-Murcia's (2008) theoretical model on communicative competence, this research conceptualized a model that could assess high school students' English communicative competence by examining relevant domestic and international studies as well as theoretical reflections. Expert opinions from a two-stage Delphi survey were compiled and incorporated to revise, supplement, and validate the English communicative competence among high school students reflecting Korea's English education environment. Following this process, the conceptual model for English communicative competence was reorganized into five sub-competences (sociolinguistic, discourse, linguistic, interactional, and strategic competence) and 15 corresponding subfactors. The content validity ratio values for the conceptual definition and factor structure of this model were all above 0.64, thus affirming the validity of the conceptual definition and factor structure.
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- 2024
24. Development and Validation of the Learning Leader Competency Test for University Students in South Korea
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Eun-Ju Choi, JuSung Jun, and Kyung-Hwa Lee
- Abstract
Background/purpose: The purpose of this study was to develop and validate the Learning Leader Competency Test in South Korean university students. Based on the analysis of previous studies, this study defined the concept of learning leader competencies, consisting of cognitive, motivational, and behavioral domains. Materials/methods. A total of 638 university students participated in the study and data were collected via online survey. Exploratory factor analysis was conducted using principal axis factoring and Oblimin rotation. Confirmatory factor analysis was performed using maximum likelihood and goodness indices such as IFI, TLI, CFI and RMSEA. Construct, convergent, discriminant, and cross-validities were tested. Results: The Learning Leader Competency Test consists of 23 items and three factors; knowledge, thinking, and problem solving; learning goal orientation and self-determination; and constructive self-expectation and caring for the community. The test's reliability (Cronbach's [alpha] = 0.856) and validity were confirmed. Conclusion: This study defines the concept of learning leader competency and identifies the subcomponents of learning leader competency into the cognitive, motivational, and behavioral domains. This test may be applied in order to determine the extent to which university students possess the competency of becoming a leader in learning.
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- 2024
25. The Effect of an Agent Tutor's Integration of Cognitive and Emotional Gestures on Cognitive Load, Motivation, and Achievement
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Soonri Choi, Soomin Kang, Kyungmin Lee, Hongjoo Ju, and Jihoon Song
- Abstract
This study proposes that the gestures of an agent tutor in a multimedia learning environment can generate positive and negative emotions in learners and influence their cognitive processes. To achieve this, we developed and integrated positive and negative agent tutor gestures in a multimedia learning environment directed by cognitive gestures. The effects of emotion type on cognition were examined in terms of cognitive load, learning motivation, and achievement. The subjects were 46 university students in Gyeonggi Province, South Korea. The students were divided into three learner groups: cognition, cognition + negative emotion, and cognition + positive emotion. The learners watched a tutorial lecture on the Notion note-taking app by an agent tutor. Data analysis was conducted using one-way ANOVA to determine the cognitive load, learning motivation, and achievement. The results showed that the positive emotion design was more effective in terms of intrinsic cognitive load, learning motivation, and achievement but had a higher extrinsic cognitive load. However, even the negative + passive group showed more positive learning than the cognition group. Although this study focused on gestures by an agent tutor, it implies that such gestures in multimedia learning contexts must be informed by emotional as well as cognitive design to provide a more meaningful learning experience.
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- 2024
26. The Cause of Institutionalized Private Tutoring in Korea: Defective Public Schooling or a Universal Desire for Family Reproduction?
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Sang Hoon Bae and Kee Ho Choi
- Abstract
Purpose: In Korea, private tutoring is considered a social evil that damages the capacity of public schooling and undermines social justice. Although the government has implemented various policies to reduce private tutoring, ranging from improving the quality of education to providing "quasi-private tutoring" programs and regulating the shadow education market, total spending on private tutoring has continued to increase. This study examines a little noticed but important cause of institutionalized private tutoring in Korea. Design/Approach/Methods: The study employed a socio-ecological perspective to analyze both education and socio-structural factors. An extensive review of the government's private tutoring reduction policies and related literature was conducted. Findings: Private tutoring functions as a means by which parents can help their children compete for admission to prestigious universities and pass on wealth and social status to their children. Participation in private tutoring has become a social norm that is taken for granted. The root causes of institutionalized private tutoring lie in both educational and socio-structural factors. Originality/Value: The study suggests that government policies, when ignoring the long-established "grammar" of parents about children's education, may either end in failure or produce unintended consequences.
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- 2024
27. Bending without Breaking - COVID-19 Tests the Resilience of State Education Policymaking Institutions. EdWorkingPaper No. 23-888
- Author
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Annenberg Institute for School Reform at Brown University, David Menefee-Libey, Carolyn Herrington, Kyoung-Jun Choi, Julie Marsh, and Katrina Bulkley
- Abstract
COVID-19 upended schooling across the United States, but with what consequences for the state-level institutions that drive most education policy? This paper reports findings on two related research questions. First, what were the most important ways state government education policymakers changed schools and schooling from the moment they began to reckon with the seriousness of COVID-19 through the first full academic year of the pandemic? Second, how deep did those changes go -- are there indications the pandemic triggered efforts to make lasting changes in states' education policymaking institutions? Using multiple-methods research focused on Colorado, Florida, Louisiana, Michigan, and Oregon, we documented policies enacted during the period from March 2020 through June 2021 across states and across sectors (traditional and choice) in three COVID-19-related education policy domains: school closings and reopenings, budgeting and resource allocation, and assessment and accountability systems. We found that states quickly enacted radical changes to policies that had taken generations to develop. They mandated sweeping school closures in Spring 2020, and then a diverse array of school reopening policies in the 2020/2021 school year. States temporarily modified their attendance-based funding systems and allocated massive federal COVID-19 relief funds. Finally, states suspended annual student testing, modified the wide array of accountability policies and programs linked to the results of those tests, and adapted to new assessment methods. These crisis-driven policy changes deeply disrupted long-established patterns and practices in education. Despite this, we found that state education governance systems remained resilient, and that at least during the first 16 months of the pandemic, stakeholders showed little interest in using the crisis to trigger more lasting institutional change. We hope these findings enable state policymakers to better prepare for future crises.
- Published
- 2023
28. Hippo-YAP/TAZ signalling coordinates adipose plasticity and energy balance by uncoupling leptin expression from fat mass.
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Choi, Sungwoo, Kang, Ju-Gyeong, Tran, Yen, Jeong, Sun-Hye, Park, Kun-Young, Shin, Hyemi, Kim, Young, Park, Myungsun, Nahmgoong, Hahn, Seol, Taejun, Jeon, Haeyon, Kim, Yeongmin, Park, Sanghee, Kim, Hee-Joo, Kim, Min-Seob, Li, Xiaoxu, Bou Sleiman, Maroun, Lee, Eries, Choi, Jinhyuk, Eisenbarth, David, Lee, Sang, Cho, Suhyeon, Auwerx, Johan, Kim, Il-Young, Kim, Jae, Park, Jong-Eun, Lim, Dae-Sik, Suh, Jae, and Moore, David
- Subjects
Animals ,Leptin ,Signal Transduction ,Energy Metabolism ,Protein Serine-Threonine Kinases ,Mice ,Adaptor Proteins ,Signal Transducing ,YAP-Signaling Proteins ,Adipose Tissue ,Adipocytes ,Hippo Signaling Pathway ,Cell Cycle Proteins ,Transcription Factors ,Transcriptional Coactivator with PDZ-Binding Motif Proteins ,Phosphoproteins ,Tumor Suppressor Proteins ,Trans-Activators - Abstract
Adipose tissues serve as an energy reservoir and endocrine organ, yet the mechanisms that coordinate these functions remain elusive. Here, we show that the transcriptional coregulators, YAP and TAZ, uncouple fat mass from leptin levels and regulate adipocyte plasticity to maintain metabolic homeostasis. Activating YAP/TAZ signalling in adipocytes by deletion of the upstream regulators Lats1 and Lats2 results in a profound reduction in fat mass by converting mature adipocytes into delipidated progenitor-like cells, but does not cause lipodystrophy-related metabolic dysfunction, due to a paradoxical increase in circulating leptin levels. Mechanistically, we demonstrate that YAP/TAZ-TEAD signalling upregulates leptin expression by directly binding to an upstream enhancer site of the leptin gene. We further show that YAP/TAZ activity is associated with, and functionally required for, leptin regulation during fasting and refeeding. These results suggest that adipocyte Hippo-YAP/TAZ signalling constitutes a nexus for coordinating adipose tissue lipid storage capacity and systemic energy balance through the regulation of adipocyte plasticity and leptin gene transcription.
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- 2024
29. Unified Asymptotics For Investment Under Illiquidity: Transaction Costs And Search Frictions
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Gang, Tae Ung and Choi, Jin Hyuk
- Subjects
Quantitative Finance - Mathematical Finance ,91G15 - Abstract
This paper investigates the optimal investment problem in a market with two types of illiquidity: transaction costs and search frictions. Extending the framework established by arXiv:2101.09936, we analyze a power-utility maximization problem where an investor encounters proportional transaction costs and trades only when a Poisson process triggers trading opportunities. We show that the optimal trading strategy is described by a no-trade region. We introduce a novel asymptotic framework applicable when both transaction costs and search frictions are small. Using this framework, we derive explicit asymptotics for the no-trade region and the value function along a specific parametric curve. This approach unifies existing asymptotic results for models dealing exclusively with either transaction costs or search frictions., Comment: 45 pages
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- 2024
30. BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-language Models
- Author
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Ye-Bin, Moon, Hyeon-Woo, Nam, Choi, Wonseok, and Oh, Tae-Hyun
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Computation and Language - Abstract
Vision language models (VLMs) perceive the world through a combination of a visual encoder and a large language model (LLM). The visual encoder, pre-trained on large-scale vision-text datasets, provides zero-shot generalization to visual data, and the LLM endows its high reasoning ability to VLMs. It leads VLMs to achieve high performance on wide benchmarks without fine-tuning, exhibiting zero or few-shot capability. However, recent studies show that VLMs are vulnerable to hallucination. This undesirable behavior degrades reliability and credibility, thereby making users unable to fully trust the output from VLMs. To enhance trustworthiness and better tackle the hallucination of VLMs, we curate a new evaluation dataset, called the BEfore-AFter hallucination dataset (BEAF), and introduce new metrics: True Understanding (TU), IGnorance (IG), StuBbornness (SB), and InDecision (ID). Unlike prior works that focus only on constructing questions and answers, the key idea of our benchmark is to manipulate visual scene information by image editing models and to design the metrics based on scene changes. This allows us to clearly assess whether VLMs correctly understand a given scene by observing the ability to perceive changes. We also visualize image-wise object relationship by virtue of our two-axis view: vision and text. Upon evaluating VLMs with our dataset, we observed that our metrics reveal different aspects of VLM hallucination that have not been reported before. Project page: \url{https://beafbench.github.io/}, Comment: Accepted at ECCV 2024. [Project Pages] https://beafbench.github.io/
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- 2024
31. DeepClair: Utilizing Market Forecasts for Effective Portfolio Selection
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Choi, Donghee, Kim, Jinkyu, Gim, Mogan, Lee, Jinho, and Kang, Jaewoo
- Subjects
Computer Science - Computational Engineering, Finance, and Science ,Computer Science - Artificial Intelligence - Abstract
Utilizing market forecasts is pivotal in optimizing portfolio selection strategies. We introduce DeepClair, a novel framework for portfolio selection. DeepClair leverages a transformer-based time-series forecasting model to predict market trends, facilitating more informed and adaptable portfolio decisions. To integrate the forecasting model into a deep reinforcement learning-driven portfolio selection framework, we introduced a two-step strategy: first, pre-training the time-series model on market data, followed by fine-tuning the portfolio selection architecture using this model. Additionally, we investigated the optimization technique, Low-Rank Adaptation (LoRA), to enhance the pre-trained forecasting model for fine-tuning in investment scenarios. This work bridges market forecasting and portfolio selection, facilitating the advancement of investment strategies., Comment: CIKM 2024 Accepted
- Published
- 2024
32. 0.7 MW Yb:YAG pumped degenerate optical parametric oscillator at 2.06 {\mu}m
- Author
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Li, Anni, Bahri, Mehran, Gray, Robert M., Choi, Seowon, Hoseinkhani, Sajjad, Srivastava, Anchit, Marandi, Alireza, and Fattahi, Hanieh
- Subjects
Physics - Optics - Abstract
Frequency comb and field-resolved broadband absorption spectroscopy are promising techniques for rapid, precise, and sensitive detection of short-lived atmospheric pollutants on-site. Enhancing detection sensitivity in absorption spectroscopy hinges on bright sources that cover molecular resonances and fast signal modulation techniques to implement lock-in detection schemes efficiently. Yb:YAG thin-disk lasers, combined with optical parametric oscillators (OPO), present a compelling solution to fulfill these requirements. In this work, we report on a bright OPO pumped by a Yb:YAG thin-disk Kerr-lens mode-locked oscillator delivering 2.8 W, 114 fs pulses at 2.06 {\mu}m with an averaged energy of 90 nJ. The OPO cavity operates at 30.9 MHz pulse repetition rates, the second harmonic of the pump cavity, allowing for broadband, efficient, and dispersion-free modulation of the OPO output pulses at 15.45 MHz rate. With 13% optical-to-optical conversion efficiency and a high-frequency intra-cavity modulation, this scalable scheme holds promise to advance the detection sensitivity and frontiers of field-resolved spectroscopic techniques.
- Published
- 2024
33. TCSpy: Multi-telescope Array Control Software for 7-Dimensional Telescope (7DT)
- Author
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Choi, Hyeonho, Im, Myungshin, and Kim, Ji Hoon
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
We introduce a novel software called TCSpy which is designed to efficiently control a multi-telescope array through network-based protocols. The primary objectives of TCSpy include centralized control of the array, support for diverse observation modes, and swift responses to the follow-up observations of astronomical transients. To achieve these objectives, TCSpy utilizes the ASCOM Alpaca protocol in conjunction with Alpyca, establishing robust communication among multiple telescope units. For the practical application of TCSpy, we implement TCSpy within the 7-Dimensional Telescope (7DT). 7DT is a telescope array consisting of 20, 0.5-m telescopes, equipped with 40 different medium-band filters. The main scientific goals of 7DT include detecting the optical counterparts of gravitational-wave sources, identifying kilonovae, and the spectral mapping of the southern sky. Through the integration of TCSpy, 7DT can achieve these scientific objectives with its unique observation modes and rapid follow-up capabilities., Comment: 8 pages, 5 figures, SPIE Astronomical Telescopes + Instrumentation 2024
- Published
- 2024
34. Superconformal Indices of 3d $\mathcal{N}=2$ SCFTs and Holography
- Author
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Bobev, Nikolay, Choi, Sunjin, Hong, Junho, and Reys, Valentin
- Subjects
High Energy Physics - Theory - Abstract
We study the superconformal index of 3d $\mathcal{N}=2$ superconformal field theories on $S^1\times_{\omega} S^2$ in the Cardy-like limit where the radius of the $S^1$ is much smaller than that of the $S^2$. We show that the first two leading terms in this Cardy-like expansion are dictated by the Bethe Ansatz formulation of the topologically twisted index of the same theory. We apply this relation to 3d $\mathcal{N}=2$ holographic superconformal field theories describing the low-energy dynamics of $N$ M2-branes and derive closed form expressions, valid to all orders in the $1/N$ expansion, for the two leading terms in the Cardy-like expansion of the superconformal index. We also discuss the implications of our results for the entropy of supersymmetric Kerr-Newman black holes in AdS$_4$ and the four-derivative corrections to 4d gauged supergravity., Comment: v1: 31 pages + appendices
- Published
- 2024
35. Using LLMs to Investigate Correlations of Conversational Follow-up Queries with User Satisfaction
- Author
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Kim, Hyunwoo, Choi, Yoonseo, Yang, Taehyun, Lee, Honggu, Park, Chaneon, Lee, Yongju, Kim, Jin Young, and Kim, Juho
- Subjects
Computer Science - Human-Computer Interaction ,Computer Science - Information Retrieval - Abstract
With large language models (LLMs), conversational search engines shift how users retrieve information from the web by enabling natural conversations to express their search intents over multiple turns. Users' natural conversation embodies rich but implicit signals of users' search intents and evaluation of search results to understand user experience with the system. However, it is underexplored how and why users ask follow-up queries to continue conversations with conversational search engines and how the follow-up queries signal users' satisfaction. From qualitative analysis of 250 conversational turns from an in-lab user evaluation of Naver Cue:, a commercial conversational search engine, we propose a taxonomy of 18 users' follow-up query patterns from conversational search, comprising two major axes: (1) users' motivations behind continuing conversations (N = 7) and (2) actions of follow-up queries (N = 11). Compared to the existing literature on query reformulations, we uncovered a new set of motivations and actions behind follow-up queries, including asking for subjective opinions or providing natural language feedback on the engine's responses. To analyze conversational search logs with our taxonomy in a scalable and efficient manner, we built an LLM-powered classifier (73% accuracy). With our classifier, we analyzed 2,061 conversational tuples collected from real-world usage logs of Cue: and examined how the conversation patterns from our taxonomy correlates with satisfaction. Our initial findings suggest some signals of dissatisfactions, such as Clarifying Queries, Excluding Condition, and Substituting Condition with follow-up queries. We envision our approach could contribute to automated evaluation of conversation search experience by providing satisfaction signals and grounds for realistic user simulations., Comment: Accepted to LLM4Eval @ SIGIR 2024 - The First Workshop on Large Language Models (LLMs) for Evaluation in Information Retrieval
- Published
- 2024
36. Unveiling the purely young star formation history of the SMC's northeastern shell from colour-magnitude diagram fitting
- Author
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Sakowska, Joanna D., Noël, Noelia E. D., Ruiz-Lara, Tomás, Gallart, Carme, Massana, Pol, Nidever, David L., Cassisi, Santi, Correa-Amaro, Patricio, Choi, Yumi, Besla, Gurtina, Erkal, Denis, Martínez-Delgado, David, Monelli, Matteo, Olsen, Knut A. G., and Stringfellow, Guy S.
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
We obtain a quantitative star formation history (SFH) of a shell-like structure ('shell') located in the northeastern part of the Small Magellanic Cloud (SMC). We use the Survey of the MAgellanic Stellar History (SMASH) to derive colour-magnitude diagrams (CMDs), reaching below the oldest main-sequence turnoff, from which we compute the SFHs with CMD fitting techniques. We present, for the first time, a novel technique that uses red clump (RC) stars from the CMDs to assess and account for the SMC's line-of-sight depth effect present during the SFH derivation. We find that accounting for this effect recovers a more accurate SFH. We quantify a 7 kpc line-of-sight depth present in the CMDs, in good agreement with depth estimates from RC stars in the northeastern SMC. By isolating the stellar content of the northeastern shell and incorporating the line-of-sight depth into our calculations, we obtain an unprecedentedly detailed SFH. We find that the northeastern shell is primarily composed of stars younger than 500 Myrs, with significant star formation enhancements around 250 Myr and 450 Myr. These young stars are the main contributors to the shell's structure. We show synchronicity between the northeastern shell's SFH with the Large Magellanic Cloud's (LMC) northern arm, which we attribute to the interaction history of the SMC with the LMC and the Milky Way (MW) over the past 500 Myr. Our results highlight the complex interplay of ram pressure stripping and the influence of the MW's circumgalactic medium in shaping the SMC's northeastern shell., Comment: 17 pages, 13 figures. Accepted to MNRAS for publication
- Published
- 2024
37. Stellar subdivisions, wedges and Buchstaber numbers
- Author
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Choi, Suyoung and Jang, Hyeontae
- Subjects
Mathematics - Combinatorics ,57S12, 14M25 - Abstract
A seed is a PL sphere that is not obtainable by a wedge operation from any other PL sphere. In this paper, we study two operations on PL spheres, known as the stellar subdivision and the wedge, that preserve the maximality of Buchstaber numbers and polytopality. We construct a new polytopal toric colorable seed from these two operations. As a corollary, we prove that the toric colorable seed inequality established by Choi and Park is tight., Comment: 6 pages
- Published
- 2024
38. Graph Signal Processing for Cross-Domain Recommendation
- Author
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Lee, Jeongeun, Kang, Seongku, Shin, Won-Yong, Choi, Jeongwhan, Park, Noseong, and Lee, Dongha
- Subjects
Computer Science - Information Retrieval ,Computer Science - Artificial Intelligence - Abstract
Cross-domain recommendation (CDR) extends conventional recommender systems by leveraging user-item interactions from dense domains to mitigate data sparsity and the cold start problem. While CDR offers substantial potential for enhancing recommendation performance, most existing CDR methods suffer from sensitivity to the ratio of overlapping users and intrinsic discrepancy between source and target domains. To overcome these limitations, in this work, we explore the application of graph signal processing (GSP) in CDR scenarios. We propose CGSP, a unified CDR framework based on GSP, which employs a cross-domain similarity graph constructed by flexibly combining target-only similarity and source-bridged similarity. By processing personalized graph signals computed for users from either the source or target domain, our framework effectively supports both inter-domain and intra-domain recommendations. Our empirical evaluation demonstrates that CGSP consistently outperforms various encoder-based CDR approaches in both intra-domain and inter-domain recommendation scenarios, especially when the ratio of overlapping users is low, highlighting its significant practical implication in real-world applications.
- Published
- 2024
39. Cheddar: A Swift Fully Homomorphic Encryption Library for CUDA GPUs
- Author
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Kim, Jongmin, Choi, Wonseok, and Ahn, Jung Ho
- Subjects
Computer Science - Cryptography and Security ,Computer Science - Performance - Abstract
Fully homomorphic encryption (FHE) is a cryptographic technology capable of resolving security and privacy problems in cloud computing by encrypting data in use. However, FHE introduces tremendous computational overhead for processing encrypted data, causing FHE workloads to become 2-6 orders of magnitude slower than their unencrypted counterparts. To mitigate the overhead, we propose Cheddar, an FHE library for CUDA GPUs, which demonstrates significantly faster performance compared to prior GPU implementations. We develop optimized functionalities at various implementation levels ranging from efficient low-level primitives to streamlined high-level operational sequences. Especially, we improve major FHE operations, including number-theoretic transform and base conversion, based on efficient kernel designs using a small word size of 32 bits. By these means, Cheddar demonstrates 2.9 to 25.6 times higher performance for representative FHE workloads compared to prior GPU implementations., Comment: 12 pages, 5 figures
- Published
- 2024
40. Trust No Bot: Discovering Personal Disclosures in Human-LLM Conversations in the Wild
- Author
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Mireshghallah, Niloofar, Antoniak, Maria, More, Yash, Choi, Yejin, and Farnadi, Golnoosh
- Subjects
Computer Science - Computation and Language - Abstract
Measuring personal disclosures made in human-chatbot interactions can provide a better understanding of users' AI literacy and facilitate privacy research for large language models (LLMs). We run an extensive, fine-grained analysis on the personal disclosures made by real users to commercial GPT models, investigating the leakage of personally identifiable and sensitive information. To understand the contexts in which users disclose to chatbots, we develop a taxonomy of tasks and sensitive topics, based on qualitative and quantitative analysis of naturally occurring conversations. We discuss these potential privacy harms and observe that: (1) personally identifiable information (PII) appears in unexpected contexts such as in translation or code editing (48% and 16% of the time, respectively) and (2) PII detection alone is insufficient to capture the sensitive topics that are common in human-chatbot interactions, such as detailed sexual preferences or specific drug use habits. We believe that these high disclosure rates are of significant importance for researchers and data curators, and we call for the design of appropriate nudging mechanisms to help users moderate their interactions.
- Published
- 2024
41. Observation of $\Lambda_c^+ \to \Lambda a_0(980)^+$ and Evidence for $\Sigma(1380)^+$ in $\Lambda_c^+ \to \Lambda \pi^+ \eta$
- Author
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BESIII Collaboration, Ablikim, M., Achasov, M. N., Adlarson, P., Afedulidis, O., Ai, X. C., Aliberti, R., Amoroso, A., An, Q., Bai, Y., Bakina, O., Balossino, I., Ban, Y., Bao, H. -R., Batozskaya, V., Begzsuren, K., Berger, N., Berlowski, M., Bertani, M., Bettoni, D., Bianchi, F., Bianco, E., Bortone, A., Boyko, I., Briere, R. A., Brueggemann, A., Cai, H., Cai, X., Calcaterra, A., Cao, G. F., Cao, N., Cetin, S. A., Chang, J. F., Che, G. R., Chelkov, G., Chen, C., Chen, C. H., Chen, Chao, Chen, G., Chen, H. S., Chen, H. Y., Chen, M. L., Chen, S. J., Chen, S. L., Chen, S. M., Chen, T., Chen, X. R., Chen, X. T., Chen, Y. B., Chen, Y. Q., Chen, Z. J., Chen, Z. Y., Choi, S. K., Cibinetto, G., Cossio, F., Cui, J. J., Dai, H. L., Dai, J. P., Dbeyssi, A., de Boer, R. E., Dedovich, D., Deng, C. Q., Deng, Z. Y., Denig, A., Denysenko, I., Destefanis, M., De Mori, F., Ding, B., Ding, X. X., Ding, Y., Dong, J., Dong, L. Y., Dong, M. Y., Dong, X., Du, M. C., Du, S. X., Duan, Y. Y., Duan, Z. H., Egorov, P., Fan, Y. H., Fang, J., Fang, S. S., Fang, W. X., Fang, Y., Fang, Y. Q., Farinelli, R., Fava, L., Feldbauer, F., Felici, G., Feng, C. Q., Feng, J. H., Feng, Y. T., Fritsch, M., Fu, C. D., Fu, J. L., Fu, Y. W., Gao, H., Gao, X. B., Gao, Y. N., Gao, Yang, Garbolino, S., Garzia, I., Ge, L., Ge, P. T., Ge, Z. W., Geng, C., Gersabeck, E. M., Gilman, A., Goetzen, K., Gong, L., Gong, W. X., Gradl, W., Gramigna, S., Greco, M., Gu, M. H., Gu, Y. T., Guan, C. Y., Guo, A. Q., Guo, L. B., Guo, M. J., Guo, R. P., Guo, Y. P., Guskov, A., Gutierrez, J., Han, K. L., Han, T. T., Hanisch, F., Hao, X. Q., Harris, F. A., He, K. K., He, K. L., Heinsius, F. H., Heinz, C. H., Heng, Y. K., Herold, C., Holtmann, T., Hong, P. C., Hou, G. Y., Hou, X. T., Hou, Y. R., Hou, Z. L., Hu, B. Y., Hu, H. M., Hu, J. F., Hu, S. L., Hu, T., Hu, Y., Huang, G. S., Huang, K. X., Huang, L. Q., Huang, X. T., Huang, Y. P., Huang, Y. S., Hussain, T., Hölzken, F., Hüsken, N., der Wiesche, N. in, Jackson, J., Janchiv, S., Jeong, J. H., Ji, Q., Ji, Q. P., Ji, W., Ji, X. B., Ji, X. L., Ji, Y. Y., Jia, X. Q., Jia, Z. K., Jiang, D., Jiang, H. B., Jiang, P. C., Jiang, S. S., Jiang, T. J., Jiang, X. S., Jiang, Y., Jiao, J. B., Jiao, J. K., Jiao, Z., Jin, S., Jin, Y., Jing, M. Q., Jing, X. M., Johansson, T., Kabana, S., Kalantar-Nayestanaki, N., Kang, X. L., Kang, X. S., Kavatsyuk, M., Ke, B. C., Khachatryan, V., Khoukaz, A., Kiuchi, R., Kolcu, O. B., Kopf, B., Kuessner, M., Kui, X., Kumar, N., Kupsc, A., Kühn, W., Lane, J. J., Larin, P., Lavezzi, L., Lei, T. T., Lei, Z. H., Lellmann, M., Lenz, T., Li, C., Li, C. H., Li, Cheng, Li, D. M., Li, F., Li, G., Li, H. B., Li, H. J., Li, H. N., Li, Hui, Li, J. R., Li, J. S., Li, K., Li, L. J., Li, L. K., Li, Lei, Li, M. H., Li, P. R., Li, Q. M., Li, Q. X., Li, R., Li, S. X., Li, T., Li, W. D., Li, W. G., Li, X., Li, X. H., Li, X. L., Li, X. Y., Li, X. Z., Li, Y. G., Li, Z. J., Li, Z. Y., Liang, C., Liang, H., Liang, Y. F., Liang, Y. T., Liao, G. R., Liao, L. Z., Liao, Y. P., Libby, J., Limphirat, A., Lin, C. C., Lin, D. X., Lin, T., Liu, B. J., Liu, B. X., Liu, C., Liu, C. X., Liu, F., Liu, F. H., Liu, Feng, Liu, G. M., Liu, H., Liu, H. B., Liu, H. H., Liu, H. M., Liu, Huihui, Liu, J. B., Liu, J. Y., Liu, K., Liu, K. Y., Liu, Ke, Liu, L., Liu, L. C., Liu, Lu, Liu, M. H., Liu, P. L., Liu, Q., Liu, S. B., Liu, T., Liu, W. K., Liu, W. M., Liu, X., Liu, Y., Liu, Y. B., Liu, Z. A., Liu, Z. D., Liu, Z. Q., Lou, X. C., Lu, F. X., Lu, H. J., Lu, J. G., Lu, X. L., Lu, Y., Lu, Y. P., Lu, Z. H., Luo, C. L., Luo, J. R., Luo, M. X., Luo, T., Luo, X. L., Lyu, X. R., Lyu, Y. F., Ma, F. C., Ma, H., Ma, H. L., Ma, J. L., Ma, L. L., Ma, M. M., Ma, Q. M., Ma, R. Q., Ma, T., Ma, X. T., Ma, X. Y., Ma, Y., Ma, Y. M., Maas, F. E., Maggiora, M., Malde, S., Mao, Y. J., Mao, Z. P., Marcello, S., Meng, Z. X., Messchendorp, J. G., Mezzadri, G., Miao, H., Min, T. J., Mitchell, R. E., Mo, X. H., Moses, B., Muchnoi, N. Yu., Muskalla, J., Nefedov, Y., Nerling, F., Nie, L. S., Nikolaev, I. B., Ning, Z., Nisar, S., Niu, Q. L., Niu, W. D., Niu, Y., Olsen, S. L., Ouyang, Q., Pacetti, S., Pan, X., Pan, Y., Pathak, A., Patteri, P., Pei, Y. P., Pelizaeus, M., Peng, H. P., Peng, Y. Y., Peters, K., Ping, J. L., Ping, R. G., Plura, S., Prasad, V., Qi, F. Z., Qi, H., Qi, H. R., Qi, M., Qi, T. Y., Qian, S., Qian, W. B., Qiao, C. F., Qiao, X. K., Qin, J. J., Qin, L. Q., Qin, L. Y., Qin, X. S., Qin, Z. H., Qiu, J. F., Qu, Z. H., Redmer, C. F., Ren, K. J., Rivetti, A., Rolo, M., Rong, G., Rosner, Ch., Ruan, S. N., Salone, N., Sarantsev, A., Schelhaas, Y., Schoenning, K., Scodeggio, M., Shan, K. Y., Shan, W., Shan, X. Y., Shang, Z. J., Shangguan, J. F., Shao, L. G., Shao, M., Shen, C. P., Shen, H. F., Shen, W. H., Shen, X. Y., Shi, B. A., Shi, H., Shi, H. C., Shi, J. L., Shi, J. Y., Shi, Q. Q., Shi, S. Y., Shi, X., Song, J. J., Song, T. Z., Song, W. M., Song, Y. J., Song, Y. X., Sosio, S., Spataro, S., Stieler, F., Su, Y. J., Sun, G. B., Sun, G. X., Sun, H., Sun, H. K., Sun, J. F., Sun, K., Sun, L., Sun, S. S., Sun, T., Sun, W. Y., Sun, Y., Sun, Y. J., Sun, Y. Z., Sun, Z. Q., Sun, Z. T., Tang, C. J., Tang, G. Y., Tang, J., Tang, M., Tang, Y. A., Tao, L. Y., Tao, Q. T., Tat, M., Teng, J. X., Thoren, V., Tian, W. H., Tian, Y., Tian, Z. F., Uman, I., Wan, Y., Wang, S. J., Wang, B., Wang, B. L., Wang, Bo, Wang, D. Y., Wang, F., Wang, H. J., Wang, J. J., Wang, J. P., Wang, K., Wang, L. L., Wang, M., Wang, N. Y., Wang, S., Wang, T., Wang, T. J., Wang, W., Wang, W. P., Wang, X., Wang, X. F., Wang, X. J., Wang, X. L., Wang, X. N., Wang, Y., Wang, Y. D., Wang, Y. F., Wang, Y. L., Wang, Y. N., Wang, Y. Q., Wang, Yaqian, Wang, Yi, Wang, Z., Wang, Z. L., Wang, Z. Y., Wang, Ziyi, Wei, D. H., Weidner, F., Wen, S. P., Wen, Y. R., Wiedner, U., Wilkinson, G., Wolke, M., Wollenberg, L., Wu, C., Wu, J. F., Wu, L. H., Wu, L. J., Wu, X., Wu, X. H., Wu, Y., Wu, Y. H., Wu, Y. J., Wu, Z., Xia, L., Xian, X. M., Xiang, B. H., Xiang, T., Xiao, D., Xiao, G. Y., Xiao, S. Y., Xiao, Y. L., Xiao, Z. J., Xie, C., Xie, X. H., Xie, Y., Xie, Y. G., Xie, Y. H., Xie, Z. P., Xing, T. Y., Xu, C. F., Xu, C. J., Xu, G. F., Xu, H. Y., Xu, M., Xu, Q. J., Xu, Q. N., Xu, W., Xu, W. L., Xu, X. P., Xu, Y. C., Xu, Z. P., Xu, Z. S., Yan, F., Yan, L., Yan, W. B., Yan, W. C., Yan, X. Q., Yang, H. J., Yang, H. L., Yang, H. X., Yang, T., Yang, Y., Yang, Y. F., Yang, Y. X., Yang, Z. W., Yao, Z. P., Ye, M., Ye, M. H., Yin, J. H., You, Z. Y., Yu, B. X., Yu, C. X., Yu, G., Yu, J. S., Yu, T., Yu, X. D., Yu, Y. C., Yuan, C. Z., Yuan, J., Yuan, L., Yuan, S. C., Yuan, Y., Yuan, Z. Y., Yue, C. X., Zafar, A. A., Zeng, F. R., Zeng, S. H., Zeng, X., Zeng, Y., Zeng, Y. J., Zhai, X. Y., Zhai, Y. C., Zhan, Y. H., Zhang, A. Q., Zhang, B. L., Zhang, B. X., Zhang, D. H., Zhang, G. Y., Zhang, H., Zhang, H. C., Zhang, H. H., Zhang, H. Q., Zhang, H. R., Zhang, H. Y., Zhang, J., Zhang, J. J., Zhang, J. L., Zhang, J. Q., Zhang, J. S., Zhang, J. W., Zhang, J. X., Zhang, J. Y., Zhang, J. Z., Zhang, Jianyu, Zhang, L. M., Zhang, Lei, Zhang, P., Zhang, Q. Y., Zhang, R. Y., Zhang, S. H., Zhang, Shulei, Zhang, X. D., Zhang, X. M., Zhang, X. Y., Zhang, Y., Zhang, Y. T., Zhang, Y. H., Zhang, Y. M., Zhang, Yan, Zhang, Z. D., Zhang, Z. H., Zhang, Z. L., Zhang, Z. Y., Zhang, Z. Z., Zhao, G., Zhao, J. Y., Zhao, J. Z., Zhao, L., Zhao, Lei, Zhao, M. G., Zhao, N., Zhao, R. P., Zhao, S. J., Zhao, Y. B., Zhao, Y. X., Zhao, Z. G., Zhemchugov, A., Zheng, B., Zheng, B. M., Zheng, J. P., Zheng, W. J., Zheng, Y. H., Zhong, B., Zhong, X., Zhou, H., Zhou, J. Y., Zhou, L. P., Zhou, S., Zhou, X., Zhou, X. K., Zhou, X. R., Zhou, X. Y., Zhou, Y. Z., Zhu, J., Zhu, K., Zhu, K. J., Zhu, K. S., Zhu, L., Zhu, L. X., Zhu, S. H., Zhu, S. Q., Zhu, T. J., Zhu, W. D., Zhu, Y. C., Zhu, Z. A., Zou, J. H., and Zu, J.
- Subjects
High Energy Physics - Experiment - Abstract
Based on $6.1~\mathrm{fb}^{-1}$ of $e^+e^-$ annihilation data collected at center-of-mass energies from 4.600~GeV to 4.843~GeV with the BESIII detector at the BEPCII collider, a partial wave analysis of $\Lambda_c^+\to\Lambda\pi^+\eta$ is performed, and branching fractions and decay asymmetry parameters of intermediate processes are determined. The process $\Lambda_c^+\to\Lambda a_0(980)^+$ is observed for the first time, and evidence for the pentaquark candidate $\Sigma(1380)^+$ decaying into $\Lambda\pi^+$ is found with statistical significance larger than $3\sigma$. The branching fraction product $\mathcal{B}(\Lambda_{c}^{+} \to \Lambda a_0(980)^+) \; \mathcal{B}( a_0(980)^+ \to \pi^{+}\eta)$ is determined to be $(1.05 \pm 0.16_{\mathrm{stat}} \pm 0.05_{\mathrm{syst}} \pm 0.07_{\mathrm{ext}})\%$, which is larger than theoretical calculations by $1 - 2$ orders of magnitude. Here the third (external) systematic is from $\mathcal{B}(\Lambda_{c}^{+} \to \Lambda \pi^+ \eta)$. Finally, we precisely obtain the absolute branching fraction $\mathcal{B}(\Lambda_{c}^{+} \to \Lambda \pi^+ \eta) = (1.94 \pm 0.07_{\mathrm{stat}} \pm 0.11_{\mathrm{syst}})\%$., Comment: 16 pages, 8 figures
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- 2024
42. DreamCatalyst: Fast and High-Quality 3D Editing via Controlling Editability and Identity Preservation
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Kim, Jiwook, Lee, Seonho, Shin, Jaeyo, Choi, Jiho, and Shim, Hyunjung
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Graphics ,Computer Science - Machine Learning - Abstract
Score distillation sampling (SDS) has emerged as an effective framework in text-driven 3D editing tasks due to its inherent 3D consistency. However, existing SDS-based 3D editing methods suffer from extensive training time and lead to low-quality results, primarily because these methods deviate from the sampling dynamics of diffusion models. In this paper, we propose DreamCatalyst, a novel framework that interprets SDS-based editing as a diffusion reverse process. Our objective function considers the sampling dynamics, thereby making the optimization process of DreamCatalyst an approximation of the diffusion reverse process in editing tasks. DreamCatalyst aims to reduce training time and improve editing quality. DreamCatalyst presents two modes: (1) a faster mode, which edits the NeRF scene in only about 25 minutes, and (2) a high-quality mode, which produces superior results in less than 70 minutes. Specifically, our high-quality mode outperforms current state-of-the-art NeRF editing methods both in terms of speed and quality. See more extensive results on our project page: https://dream-catalyst.github.io.
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- 2024
43. Team HYU ASML ROBOVOX SP Cup 2024 System Description
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Choi, Jeong-Hwan, Kim, Gaeun, Lee, Hee-Jae, Ahn, Seyun, Kim, Hyun-Soo, and Chang, Joon-Hyuk
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Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
This report describes the submission of HYU ASML team to the IEEE Signal Processing Cup 2024 (SP Cup 2024). This challenge, titled "ROBOVOX: Far-Field Speaker Recognition by a Mobile Robot," focuses on speaker recognition using a mobile robot in noisy and reverberant conditions. Our solution combines the result of deep residual neural networks and time-delay neural network-based speaker embedding models. These models were trained on a diverse dataset that includes French speech. To account for the challenging evaluation environment characterized by high noise, reverberation, and short speech conditions, we focused on data augmentation and training speech duration for the speaker embedding model. Our submission achieved second place on the SP Cup 2024 public leaderboard, with a detection cost function of 0.5245 and an equal error rate of 6.46%., Comment: Technical report for IEEE Signal Processing Cup 2024, 9 pages
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- 2024
44. Development of MMC-based lithium molybdate cryogenic calorimeters for AMoRE-II
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Agrawal, A., Alenkov, V. V., Aryal, P., Bae, H., Beyer, J., Bhandari, B., Boiko, R. S., Boonin, K., Buzanov, O., Byeon, C. R., Chanthima, N., Cheoun, M. K., Choe, J. S., Choi, S., Choudhury, S., Chung, J. S., Danevich, F. A., Djamal, M., Drung, D., Enss, C., Fleischmann, A., Gangapshev, A. M., Gastaldo, L., Gavrilyuk, Y. M., Gezhaev, A. M., Gileva, O., Grigorieva, V. D., Gurentsov, V. I., Ha, C., Ha, D. H., Ha, E. J., Hwang, D. H., Jeon, E. J., Jeon, J. A., Jo, H. S., Kaewkhao, J., Kang, C. S., Kang, W. G., Kazalov, V. V., Kempf, S., Khan, A., Khan, S., Kim, D. Y., Kim, G. W., Kim, H. B., Kim, H. J., Kim, H. L., Kim, H. S., Kim, M. B., Kim, S. C., Kim, S. K., Kim, S. R., Kim, W. T., Kim, Y. D., Kim, Y. H., Kirdsiri, K., Ko, Y. J., Kobychev, V. V., Kornoukhov, V., Kuzminov, V. V., Kwon, D. H., Lee, C. H., Lee, D. Y., Lee, E. K., Lee, H. J., Lee, H. S., Lee, J., Lee, J. Y., Lee, K. B., Lee, M. H., Lee, M. K., Lee, S. W., Lee, Y. C., Leonard, D. S., Lim, H. S., Mailyan, B., Makarov, E. P., Nyanda, P., Oh, Y., Olsen, S. L., Panasenko, S. I., Park, H. K., Park, H. S., Park, K. S., Park, S. Y., Polischuk, O. G., Prihtiadi, H., Ra, S., Ratkevich, S. S., Rooh, G., Sari, M. B., Seo, J., Seo, K. M., Sharma, B., Shin, K. A., Shlegel, V. N., Siyeon, K., So, J., Sokur, N. V., Son, J. K., Song, J. W., Srisittipokakun, N., Tretyak, V. I., Wirawan, R., Woo, K. R., Yeon, H. J., Yoon, Y. S., and Yue, Q.
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Physics - Instrumentation and Detectors ,Astrophysics - Instrumentation and Methods for Astrophysics ,High Energy Physics - Experiment ,Nuclear Experiment - Abstract
The AMoRE collaboration searches for neutrinoless double beta decay of $^{100}$Mo using molybdate scintillating crystals via low temperature thermal calorimetric detection. The early phases of the experiment, AMoRE-pilot and AMoRE-I, have demonstrated competitive discovery potential. Presently, the AMoRE-II experiment, featuring a large detector array with about 90 kg of $^{100}$Mo isotope, is under construction.This paper discusses the baseline design and characterization of the lithium molybdate cryogenic calorimeters to be used in the AMoRE-II detector modules. The results from prototype setups that incorporate new housing structures and two different crystal masses (316 g and 517 - 521 g), operated at 10 mK temperature, show energy resolutions (FWHM) of 7.55 - 8.82 keV at the 2.615 MeV $^{208}$Tl $\gamma$ line, and effective light detection of 0.79 - 0.96 keV/MeV. The simultaneous heat and light detection enables clear separation of alpha particles with a discrimination power of 12.37 - 19.50 at the energy region around $^6$Li(n, $\alpha$)$^3$H with Q-value = 4.785 MeV. Promising detector performances were demonstrated at temperatures as high as 30 mK, which relaxes the temperature constraints for operating the large AMoRE-II array.
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- 2024
45. Click-Gaussian: Interactive Segmentation to Any 3D Gaussians
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Choi, Seokhun, Song, Hyeonseop, Kim, Jaechul, Kim, Taehyeong, and Do, Hoseok
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Graphics - Abstract
Interactive segmentation of 3D Gaussians opens a great opportunity for real-time manipulation of 3D scenes thanks to the real-time rendering capability of 3D Gaussian Splatting. However, the current methods suffer from time-consuming post-processing to deal with noisy segmentation output. Also, they struggle to provide detailed segmentation, which is important for fine-grained manipulation of 3D scenes. In this study, we propose Click-Gaussian, which learns distinguishable feature fields of two-level granularity, facilitating segmentation without time-consuming post-processing. We delve into challenges stemming from inconsistently learned feature fields resulting from 2D segmentation obtained independently from a 3D scene. 3D segmentation accuracy deteriorates when 2D segmentation results across the views, primary cues for 3D segmentation, are in conflict. To overcome these issues, we propose Global Feature-guided Learning (GFL). GFL constructs the clusters of global feature candidates from noisy 2D segments across the views, which smooths out noises when training the features of 3D Gaussians. Our method runs in 10 ms per click, 15 to 130 times as fast as the previous methods, while also significantly improving segmentation accuracy. Our project page is available at https://seokhunchoi.github.io/Click-Gaussian, Comment: Accepted to ECCV 2024. The first two authors contributed equally to this work
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- 2024
46. SlingBAG: Sliding ball adaptive growth algorithm with differentiable radiation enables super-efficient iterative 3D photoacoustic image reconstruction
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Li, Shuang, Wang, Yibing, Gao, Jian, Kim, Chulhong, Choi, Seongwook, Zhang, Yu, Chen, Qian, Yao, Yao, and Li, Changhui
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
High-quality 3D photoacoustic imaging (PAI) reconstruction under sparse view or limited view has long been challenging. Traditional 3D iterative-based reconstruction methods suffer from both slow speed and high memory consumption. Recently, in computer graphics, the differentiable rendering has made significant progress, particularly with the rise of 3D Gaussian Splatting. Inspired by these, we introduce differentiable radiation into PAI, developing a novel reconstruction algorithm: the Sliding Ball Adaptive Growth algorithm (SlingBAG) for 3D PAI, which shows ability in high-quality 3D PAI reconstruction both under extremely sparse view and limited view. We established the point cloud dataset in PAI, and used unique differentiable rapid radiator based on the spherical decomposition strategy and the randomly initialized point cloud adaptively optimized according to sparse sensor data. Each point undergoes updates in 3D coordinates, initial pressure, and resolution (denoted by the radius of ball). Points undergo adaptive growth during iterative process, including point destroying, splitting and duplicating along the gradient of their positions, manifesting the sliding ball effect. Finally, our point cloud to voxel grid shader renders the final reconstruction results. Simulation and in vivo experiments demonstrate that our SlingBAG reconstruction result's SNR can be more than 40 dB under extremely sparse view, while the SNR of traditional back-projection algorithm's result is less than 20 dB. Moreover, the result of SlingBAG's structural similarity to the ground truth is significantly higher, with an SSIM value of 95.6%. Notably, our differentiable rapid radiator can conduct forward PA simulation in homogeneous, non-viscous media substantially faster than current methods that numerically simulate the wave propagation, such as k-Wave. The dataset and all code will be open source.
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- 2024
47. Measurement of the branching fraction of $D^+_s\to \ell^+\nu_\ell$ via $e^+e^-\to D^{*+}_{s} D^{*-}_{s}$
- Author
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BESIII Collaboration, Ablikim, M., Achasov, M. N., Adlarson, P., Afedulidis, O., Ai, X. C., Aliberti, R., Amoroso, A., An, Q., Bai, Y., Bakina, O., Balossino, I., Ban, Y., Bao, H. -R., Batozskaya, V., Begzsuren, K., Berger, N., Berlowski, M., Bertani, M., Bettoni, D., Bianchi, F., Bianco, E., Bortone, A., Boyko, I., Briere, R. A., Brueggemann, A., Cai, H., Cai, X., Calcaterra, A., Cao, G. F., Cao, N., Cetin, S. A., Chang, J. F., Che, G. R., Chelkov, G., Chen, C., Chen, C. H., Chen, Chao, Chen, G., Chen, H. S., Chen, H. Y., Chen, M. L., Chen, S. J., Chen, S. L., Chen, S. M., Chen, T., Chen, X. R., Chen, X. T., Chen, Y. B., Chen, Y. Q., Chen, Z. J., Chen, Z. Y., Choi, S. K., Cibinetto, G., Cossio, F., Cui, J. J., Dai, H. L., Dai, J. P., Dbeyssi, A., de Boer, R. E., Dedovich, D., Deng, C. Q., Deng, Z. Y., Denig, A., Denysenko, I., Destefanis, M., De Mori, F., Ding, B., Ding, X. X., Ding, Y., Dong, J., Dong, L. Y., Dong, M. Y., Dong, X., Du, M. C., Du, S. X., Duan, Y. Y., Duan, Z. H., Egorov, P., Fan, Y. H., Fang, J., Fang, S. S., Fang, W. X., Fang, Y., Fang, Y. Q., Farinelli, R., Fava, L., Feldbauer, F., Felici, G., Feng, C. Q., Feng, J. H., Feng, Y. T., Fritsch, M., Fu, C. D., Fu, J. L., Fu, Y. W., Gao, H., Gao, X. B., Gao, Y. N., Gao, Yang, Garbolino, S., Garzia, I., Ge, L., Ge, P. T., Ge, Z. W., Geng, C., Gersabeck, E. M., Gilman, A., Goetzen, K., Gong, L., Gong, W. X., Gradl, W., Gramigna, S., Greco, M., Gu, M. H., Gu, Y. T., Guan, C. Y., Guo, A. Q., Guo, L. B., Guo, M. J., Guo, R. P., Guo, Y. P., Guskov, A., Gutierrez, J., Han, K. L., Han, T. T., Hanisch, F., Hao, X. Q., Harris, F. A., He, K. K., He, K. L., Heinsius, F. H., Heinz, C. H., Heng, Y. K., Herold, C., Holtmann, T., Hong, P. C., Hou, G. Y., Hou, X. T., Hou, Y. R., Hou, Z. L., Hu, B. Y., Hu, H. M., Hu, J. F., Hu, S. L., Hu, T., Hu, Y., Huang, G. S., Huang, K. X., Huang, L. Q., Huang, X. T., Huang, Y. P., Huang, Y. S., Hussain, T., Hölzken, F., Hüsken, N., der Wiesche, N. in, Jackson, J., Janchiv, S., Jeong, J. H., Ji, Q., Ji, Q. P., Ji, W., Ji, X. B., Ji, X. L., Ji, Y. Y., Jia, X. Q., Jia, Z. K., Jiang, D., Jiang, H. B., Jiang, P. C., Jiang, S. S., Jiang, T. J., Jiang, X. S., Jiang, Y., Jiao, J. B., Jiao, J. K., Jiao, Z., Jin, S., Jin, Y., Jing, M. Q., Jing, X. M., Johansson, T., Kabana, S., Kalantar-Nayestanaki, N., Kang, X. L., Kang, X. S., Kavatsyuk, M., Ke, B. C., Khachatryan, V., Khoukaz, A., Kiuchi, R., Kolcu, O. B., Kopf, B., Kuessner, M., Kui, X., Kumar, N., Kupsc, A., Kühn, W., Lane, J. J., Lavezzi, L., Lei, T. T., Lei, Z. H., Lellmann, M., Lenz, T., Li, C., Li, C. H., Li, Cheng, Li, D. M., Li, F., Li, G., Li, H. B., Li, H. J., Li, H. N., Li, Hui, Li, J. R., Li, J. S., Li, K., Li, L. J., Li, L. K., Li, Lei, Li, M. H., Li, P. R., Li, Q. M., Li, Q. X., Li, R., Li, S. X., Li, T., Li, W. D., Li, W. G., Li, X., Li, X. H., Li, X. L., Li, X. Y., Li, X. Z., Li, Y. G., Li, Z. J., Li, Z. 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- Subjects
High Energy Physics - Experiment ,High Energy Physics - Phenomenology - Abstract
Based on $10.64~\mathrm{fb}^{-1}$ of $e^+e^-$ collision data taken at center-of-mass energies between 4.237 and 4.699 GeV with the BESIII detector, we study the leptonic $D^+_s$ decays using the $e^+e^-\to D^{*+}_{s} D^{*-}_{s}$ process. The branching fractions of $D_s^+\to\ell^+\nu_{\ell}\,(\ell=\mu,\tau)$ are measured to be $\mathcal{B}(D_s^+\to\mu^+\nu_\mu)=(0.547\pm0.026_{\rm stat}\pm0.016_{\rm syst})\%$ and $\mathcal{B}(D_s^+\to\tau^+\nu_\tau)=(5.60\pm0.16_{\rm stat}\pm0.20_{\rm syst})\%$, respectively. The product of the decay constant and Cabibbo-Kobayashi-Maskawa matrix element $|V_{cs}|$ is determined to be $f_{D_s^+}|V_{cs}|=(246.5\pm5.9_{\rm stat}\pm3.6_{\rm syst}\pm0.5_{\rm input})_{\mu\nu}~\mathrm{MeV}$ and $f_{D_s^+}|V_{cs}|=(252.7\pm3.6_{\rm stat}\pm4.5_{\rm syst}\pm0.6_{\rm input}))_{\tau \nu}~\mathrm{MeV}$, respectively. Taking the value of $|V_{cs}|$ from a global fit in the Standard Model, we obtain ${f_{D^+_s}}=(252.8\pm6.0_{\rm stat}\pm3.7_{\rm syst}\pm0.6_{\rm input})_{\mu\nu}$ MeV and ${f_{D^+_s}}=(259.2\pm3.6_{\rm stat}\pm4.5_{\rm syst}\pm0.6_{\rm input})_{\tau \nu}$ MeV, respectively. Conversely, taking the value for $f_{D_s^+}$ from the latest lattice quantum chromodynamics calculation, we obtain $|V_{cs}| =(0.986\pm0.023_{\rm stat}\pm0.014_{\rm syst}\pm0.003_{\rm input})_{\mu\nu}$ and $|V_{cs}| = (1.011\pm0.014_{\rm stat}\pm0.018_{\rm syst}\pm0.003_{\rm input})_{\tau \nu}$, respectively., Comment: 27 pages, 13 figures
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- 2024
48. I$^2$-SLAM: Inverting Imaging Process for Robust Photorealistic Dense SLAM
- Author
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Bae, Gwangtak, Choi, Changwoon, Heo, Hyeongjun, Kim, Sang Min, and Kim, Young Min
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
We present an inverse image-formation module that can enhance the robustness of existing visual SLAM pipelines for casually captured scenarios. Casual video captures often suffer from motion blur and varying appearances, which degrade the final quality of coherent 3D visual representation. We propose integrating the physical imaging into the SLAM system, which employs linear HDR radiance maps to collect measurements. Specifically, individual frames aggregate images of multiple poses along the camera trajectory to explain prevalent motion blur in hand-held videos. Additionally, we accommodate per-frame appearance variation by dedicating explicit variables for image formation steps, namely white balance, exposure time, and camera response function. Through joint optimization of additional variables, the SLAM pipeline produces high-quality images with more accurate trajectories. Extensive experiments demonstrate that our approach can be incorporated into recent visual SLAM pipelines using various scene representations, such as neural radiance fields or Gaussian splatting., Comment: ECCV 2024
- Published
- 2024
49. Real toric manifolds associated with chordal nestohedra
- Author
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Choi, Suyoung and Yoon, Younghan
- Subjects
Mathematics - Algebraic Topology ,Mathematics - Algebraic Geometry ,Mathematics - Combinatorics ,57S12, 14M25, 57N65, 05A05, 52B22 - Abstract
This paper investigates the rational Betti numbers of real toric manifolds associated with chordal nestohedra. We consider the poset topology of a specific poset induced from a chordal building set, and show its EL-shellability. Based on this, we present an explicit description using alternating $\mathcal{B}$-permutations for a chordal building set $\mathcal{B}$, transforming the computing Betti numbers into a counting problem. This approach allows us to compute the $a$-number of a finite simple graph through permutation counting when the graph is chordal. In addition, we provide detailed computations for specific cases such as real Hochschild varieties corresponding to Hochschild polytopes., Comment: 26 pages,6 figures, 3 tables
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- 2024
50. Multibeam Satellite Communications with Massive MIMO: Asymptotic Performance Analysis and Design Insights
- Author
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Kim, Seyong, Choi, Jinseok, Shin, Wonjae, Lee, Namyoon, and Park, Jeonghun
- Subjects
Computer Science - Information Theory - Abstract
To achieve high performance without substantial overheads associated with channel state information (CSI) of ground users, we consider a fixed-beam precoding approach, where a satellite forms multiple fixed-beams without relying on CSI, then select a suitable user set for each beam. Upon this precoding method, we put forth a satellite equipped with massive multiple-input multiple-output (MIMO), by which inter-beam interference is efficiently mitigated by narrowing corresponding beam width. By modeling the ground users' locations via a Poisson point process, we rigorously analyze the achievable performance of the presented multibeam satellite system. In particular, we investigate the asymptotic scaling laws that reveal the interplay between the user density, the number of beams, and the number of antennas. Our analysis offers critical design insights for the multibeam satellite with massive MIMO: i) If the user density scales in power with the number of antennas, the considered precoding can achieve a linear fraction of the optimal rate in the asymptotic regime. ii) A certain additional scaling factor for the user density is needed as the number of beams increases to maintain the asymptotic optimality.
- Published
- 2024
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