Search

Your search keyword '"Vij A"' showing total 15,872 results
Start Over Author "Vij A"
15,872 results on '"Vij A"'

1. GiGL: Large-Scale Graph Neural Networks at Snapchat

Author

Zhao, Tong, Liu, Yozen, Kolodner, Matthew, Montemayor, Kyle, Ghazizadeh, Elham, Batra, Ankit, Fan, Zihao, Gao, Xiaobin, Guo, Xuan, Ren, Jiwen, Park, Serim, Yu, Peicheng, Yu, Jun, Vij, Shubham, and Shah, Neil

Subjects
Computer Science - Machine Learning
Abstract

Recent advances in graph machine learning (ML) with the introduction of Graph Neural Networks (GNNs) have led to a widespread interest in applying these approaches to business applications at scale. GNNs enable differentiable end-to-end (E2E) learning of model parameters given graph structure which enables optimization towards popular node, edge (link) and graph-level tasks. While the research innovation in new GNN layers and training strategies has been rapid, industrial adoption and utility of GNNs has lagged considerably due to the unique scale challenges that large-scale graph ML problems create. In this work, we share our approach to training, inference, and utilization of GNNs at Snapchat. To this end, we present GiGL (Gigantic Graph Learning), an open-source library to enable large-scale distributed graph ML to the benefit of researchers, ML engineers, and practitioners. We use GiGL internally at Snapchat to manage the heavy lifting of GNN workflows, including graph data preprocessing from relational DBs, subgraph sampling, distributed training, inference, and orchestration. GiGL is designed to interface cleanly with open-source GNN modeling libraries prominent in academia like PyTorch Geometric (PyG), while handling scaling and productionization challenges that make it easier for internal practitioners to focus on modeling. GiGL is used in multiple production settings, and has powered over 35 launches across multiple business domains in the last 2 years in the contexts of friend recommendation, content recommendation and advertising. This work details high-level design and tools the library provides, scaling properties, case studies in diverse business settings with industry-scale graphs, and several key lessons learned in employing graph ML at scale on large social data. GiGL is open-sourced at https://github.com/snap-research/GiGL.

Published
2025

2. LATTEO: A Framework to Support Learning Asynchronously Tempered with Trusted Execution and Obfuscation

Author

Kumar, Abhinav, Torres, George, Guzinski, Noah, Panwar, Gaurav, Tourani, Reza, Misra, Satyajayant, Spoczynski, Marcin, Vij, Mona, and Himayat, Nageen

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

The privacy vulnerabilities of the federated learning (FL) paradigm, primarily caused by gradient leakage, have prompted the development of various defensive measures. Nonetheless, these solutions have predominantly been crafted for and assessed in the context of synchronous FL systems, with minimal focus on asynchronous FL. This gap arises in part due to the unique challenges posed by the asynchronous setting, such as the lack of coordinated updates, increased variability in client participation, and the potential for more severe privacy risks. These concerns have stymied the adoption of asynchronous FL. In this work, we first demonstrate the privacy vulnerabilities of asynchronous FL through a novel data reconstruction attack that exploits gradient updates to recover sensitive client data. To address these vulnerabilities, we propose a privacy-preserving framework that combines a gradient obfuscation mechanism with Trusted Execution Environments (TEEs) for secure asynchronous FL aggregation at the network edge. To overcome the limitations of conventional enclave attestation, we introduce a novel data-centric attestation mechanism based on Multi-Authority Attribute-Based Encryption. This mechanism enables clients to implicitly verify TEE-based aggregation services, effectively handle on-demand client participation, and scale seamlessly with an increasing number of asynchronous connections. Our gradient obfuscation mechanism reduces the structural similarity index of data reconstruction by 85% and increases reconstruction error by 400%, while our framework improves attestation efficiency by lowering average latency by up to 1500% compared to RA-TLS, without additional overhead.

Published
2025

3. Fine-tuning Language Models for Recipe Generation: A Comparative Analysis and Benchmark Study

Author

Vij, Anneketh, Liu, Changhao, Nair, Rahul Anil, Ho, Theodore Eugene, Shi, Edward, and Bhowmick, Ayan

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

This research presents an exploration and study of the recipe generation task by fine-tuning various very small language models, with a focus on developing robust evaluation metrics and comparing across different language models the open-ended task of recipe generation. This study presents extensive experiments with multiple model architectures, ranging from T5-small (Raffel et al., 2023) and SmolLM-135M(Allal et al., 2024) to Phi-2 (Research, 2023), implementing both traditional NLP metrics and custom domain-specific evaluation metrics. Our novel evaluation framework incorporates recipe-specific metrics for assessing content quality and introduces approaches to allergen substitution. The results indicate that, while larger models generally perform better on standard metrics, the relationship between model size and recipe quality is more nuanced when considering domain-specific metrics. SmolLM-360M and SmolLM-1.7B demonstrate comparable performance despite their size difference before and after fine-tuning, while fine-tuning Phi-2 shows notable limitations in recipe generation despite its larger parameter count. The comprehensive evaluation framework and allergen substitution systems provide valuable insights for future work in recipe generation and broader NLG tasks that require domain expertise and safety considerations., Comment: 18 pages, 10 figures,14 tables

Published
2025

4. Productivity of Short Term Assets as a Signal of Future Stock Performance

Author

Vohra, Veer, Vij, Devyani, Mehta, Jehil, and Ozcan, Arman

Subjects
Quantitative Finance - Trading and Market Microstructure
Abstract

This paper investigates cash productivity as a signal for future stock performance, building on the cash-return framework of Faulkender and Wang (2006). Using financial and market data from WRDS, we calculate cash returns as a proxy for operational efficiency and evaluate a long-only strategy applied to Nasdaq-listed non-financial firms. Results show limited predictive power across the broader Nasdaq universe but strong performance in a handpicked portfolio, which achieves significant positive alpha after controlling for the Fama-French three factors. These findings underscore the importance of refined universe selection. While promising, the strategy requires further validation, including the incorporation of transaction costs and performance testing across economic cycles. Our results suggest that cash productivity, when combined with other complementary signals and careful universe selection, can be a valuable tool for generating excess returns.

Published
2024

5. Colossal Dielectric Permittivity and Superparaelectricity in phenyl pyrimidine based liquid crystals

Author

Panarin, Yuri P., Jiang, Wanhe, Yadav, Neelam, Sahai, Mudit, Tang, Yumin, Zeng, Xiangbing, Panarina, O. E., Mehl, Georg H., and Vij, Jagdish K.

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

A set of polar rod-shaped liquid crystalline molecules with large dipole moments (mu > 10.4-14.8 D), their molecular structures based on the ferroelectric nematic prototype DIO, are designed, synthesized, and investigated. When the penultimate fluoro-phenyl ring is replaced by phenylpyrimidine moiety, the molecular dipole moment increases from 9.4 D for DIO to 10.4 D for the new molecule and when the terminal fluoro-group is additionally replaced by the nitrile group, the dipole moment rises to 14.8 D. Such a replacement enhances not only the net dipole moment of the molecule, but it also reduces the steric hindrance to rotations of the moieties within the molecule. The superparaelectric nematic (N) and smectic A (SmA) phases of these compounds are found to exhibit colossal dielectric permittivity, obtained both from dielectric spectroscopy, and capacitance measurements using a simple capacitor divider circuit. The electric polarization is measured vs. the field (E). However, no hysteresis in P vs. E is found in the nematic and smectic A phases. The colossal dielectric permittivity persists over the entire fluidic range. The experimental results lead us to conclude that these materials belong to the class of superparaelectrics (SPE) rather than to ferroelectrics due to the absence hysteresis and linear P vs E dependence. The synthesized organic materials are the first fluids for which superparaelectricity is discovered and furthermore these show great potential for the applications in supercapacitors used in storing energy., Comment: 24 pages, 7 figures, 1 table. Submited to JMC C

Published
2024

6. Coherent spectroscopy of a single Mn-doped InGaAs quantum dot

Author

Filipovic, Jovana, Kundu, Ankit, Vij, Neelesh Kumar, Fécherolle, Simon, Lemaître, Aristide, Gupta, Shilpi, and Krebs, Olivier

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Quantum Physics
Abstract

Doping a self-assembled InGaAs/GaAs quantum dot (QD) with a single Mn atom, a magnetic acceptor impurity, provides a quantum system with discrete energy levels and original spin-dependent optical selection rules, which thus has large potential in quantum photonics, notably as a source of multi-entangled photons. To investigate this potential further, we perform coherent optical spectroscopy under continuous wave excitation of the 3-level V-like system formed in such a Mn-doped QD when charged by a single hole. In spite of a large inhomogeneous broadening of the optical transitions, we demonstrate Autler-Townes splitting both by resonant Raman scattering and by probe absorption spectroscopy for different saturation powers. Analysing these data with a comprehensive model based on optical Bloch equations, we show evidence for quantum interference within the V-like system and assess the pure dephasing rate between the corresponding spin states., Comment: 10 pages, 6 figures

Published
2024

7. Fortify Your Foundations: Practical Privacy and Security for Foundation Model Deployments In The Cloud

Author

Chrapek, Marcin, Vahldiek-Oberwagner, Anjo, Spoczynski, Marcin, Constable, Scott, Vij, Mona, and Hoefler, Torsten

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract

Foundation Models (FMs) display exceptional performance in tasks such as natural language processing and are being applied across a growing range of disciplines. Although typically trained on large public datasets, FMs are often fine-tuned or integrated into Retrieval-Augmented Generation (RAG) systems, which rely on private data. This access, along with their size and costly training, heightens the risk of intellectual property theft. Moreover, multimodal FMs may expose sensitive information. In this work, we examine the FM threat model and discuss the practicality and comprehensiveness of various approaches for securing against them, such as ML-based methods and trusted execution environments (TEEs). We demonstrate that TEEs offer an effective balance between strong security properties, usability, and performance. Specifically, we present a solution achieving less than 10\% overhead versus bare metal for the full Llama2 7B and 13B inference pipelines running inside \intel\ SGX and \intel\ TDX. We also share our configuration files and insights from our implementation. To our knowledge, our work is the first to show the practicality of TEEs for securing FMs.

Published
2024

8. Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries

Author

Vodrahalli, Kiran, Ontanon, Santiago, Tripuraneni, Nilesh, Xu, Kelvin, Jain, Sanil, Shivanna, Rakesh, Hui, Jeffrey, Dikkala, Nishanth, Kazemi, Mehran, Fatemi, Bahare, Anil, Rohan, Dyer, Ethan, Shakeri, Siamak, Vij, Roopali, Mehta, Harsh, Ramasesh, Vinay, Le, Quoc, Chi, Ed, Lu, Yifeng, Firat, Orhan, Lazaridou, Angeliki, Lespiau, Jean-Baptiste, Attaluri, Nithya, and Olszewska, Kate

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

We introduce Michelangelo: a minimal, synthetic, and unleaked long-context reasoning evaluation for large language models which is also easy to automatically score. This evaluation is derived via a novel, unifying framework for evaluations over arbitrarily long contexts which measure the model's ability to do more than retrieve a single piece of information from its context. The central idea of the Latent Structure Queries framework (LSQ) is to construct tasks which require a model to ``chisel away'' the irrelevant information in the context, revealing a latent structure in the context. To verify a model's understanding of this latent structure, we query the model for details of the structure. Using LSQ, we produce three diagnostic long-context evaluations across code and natural-language domains intended to provide a stronger signal of long-context language model capabilities. We perform evaluations on several state-of-the-art models and demonstrate both that a) the proposed evaluations are high-signal and b) that there is significant room for improvement in synthesizing long-context information.

Published
2024

9. Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes.

Author

Skerget, Sheri, Penaherrera, Daniel, Chari, Ajai, Jagannath, Sundar, Siegel, David, Vij, Ravi, Orloff, Gregory, Jakubowiak, Andrzej, Niesvizky, Ruben, Liles, Darla, Berdeja, Jesus, Levy, Moshe, Wolf, Jeffrey, Usmani, Saad, Christofferson, Austin, Nasser, Sara, Aldrich, Jessica, Legendre, Christophe, Benard, Brooks, Miller, Chase, Turner, Bryce, Kurdoglu, Ahmet, Washington, Megan, Yellapantula, Venkata, Adkins, Jonathan, Cuyugan, Lori, Boateng, Martin, Helland, Adrienne, Kyman, Shari, McDonald, Jackie, Reiman, Rebecca, Stephenson, Kristi, Tassone, Erica, Blanski, Alex, Livermore, Brianne, Kirchhoff, Meghan, Rohrer, Daniel, DAgostino, Mattia, Gamella, Manuela, Collison, Kimberly, Stumph, Jennifer, Kidd, Pam, Donnelly, Andrea, Zaugg, Barbara, Toone, Maureen, McBride, Kyle, DeRome, Mary, Rogers, Jennifer, Craig, David, Liang, Winnie, Gutierrez, Norma, Jewell, Scott, Carpten, John, Anderson, Kenneth, Cho, Hearn, Auclair, Daniel, Lonial, Sagar, and Keats, Jonathan

Subjects
Humans, Multiple Myeloma, DNA Copy Number Variations, Gene Expression Regulation, Neoplastic, Exome Sequencing, Gene Expression Profiling, Female, Male, Whole Genome Sequencing, Longitudinal Studies, Disease Progression, Middle Aged
Abstract

Multiple myeloma is a treatable, but currently incurable, hematological malignancy of plasma cells characterized by diverse and complex tumor genetics for which precision medicine approaches to treatment are lacking. The Multiple Myeloma Research Foundations Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile study ( NCT01454297 ) is a longitudinal, observational clinical study of newly diagnosed patients with multiple myeloma (n = 1,143) where tumor samples are characterized using whole-genome sequencing, whole-exome sequencing and RNA sequencing at diagnosis and progression, and clinical data are collected every 3 months. Analyses of the baseline cohort identified genes that are the target of recurrent gain-of-function and loss-of-function events. Consensus clustering identified 8 and 12 unique copy number and expression subtypes of myeloma, respectively, identifying high-risk genetic subtypes and elucidating many of the molecular underpinnings of these unique biological groups. Analysis of serial samples showed that 25.5% of patients transition to a high-risk expression subtype at progression. We observed robust expression of immunotherapy targets in this subtype, suggesting a potential therapeutic option.

Published
2024

10. Domain Adaptation of Llama3-70B-Instruct through Continual Pre-Training and Model Merging: A Comprehensive Evaluation

Author

Siriwardhana, Shamane, McQuade, Mark, Gauthier, Thomas, Atkins, Lucas, Neto, Fernando Fernandes, Meyers, Luke, Vij, Anneketh, Odenthal, Tyler, Goddard, Charles, MacCarthy, Mary, and Solawetz, Jacob

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We conducted extensive experiments on domain adaptation of the Meta-Llama-3-70B-Instruct model on SEC data, exploring its performance on both general and domain-specific benchmarks. Our focus included continual pre-training (CPT) and model merging, aiming to enhance the model's domain-specific capabilities while mitigating catastrophic forgetting. Through this study, we evaluated the impact of integrating financial regulatory data into a robust language model and examined the effectiveness of our model merging techniques in preserving and improving the model's instructive abilities. The model is accessible at hugging face: https://huggingface.co/arcee-ai/Llama-3-SEC-Base, arcee-ai/Llama-3-SEC-Base. This is an intermediate checkpoint of our final model, which has seen 20B tokens so far. The full model is still in the process of training. This is a preprint technical report with thorough evaluations to understand the entire process., Comment: 8 pages, 6 figures

Published
2024

11. Acute-on-chronic liver failure (ACLF): the ‘Kyoto Consensus’—steps from Asia

Author

Choudhury, Ashok, Kulkarni, Anand V., Arora, Vinod, Soin, A. S., Dokmeci, Abdul Kadir, Chowdhury, Abhijeet, Koshy, Abraham, Duseja, Ajay, Kumar, Ajay, Mishra, Ajay Kumar, Patwa, Ajay Kumar, Sood, Ajit, Roy, Akash, Shukla, Akash, Chan, Albert, Krag, Aleksander, Mukund, Amar, Mandot, Ameet, Goel, Amit, Butt, Amna Subhan, Sahney, Amrish, Shrestha, Ananta, Cárdenas, Andrés, Di Giorgio, Angelo, Arora, Anil, Anand, Anil Chandra, Dhawan, Anil, Jindal, Ankur, Saraya, Anoop, Srivastava, Anshu, Kumar, Anupam, Kaewdech, Apichat, Pande, Apurva, Rastogi, Archana, Valsan, Arun, Goel, Ashish, Kumar, Ashish, Singal, Ashwani K., Tanaka, Atsushi, Coilly, Audrey, Singh, Ayaskanta, Meena, Babu Lal, Jagadisan, Barath, Sharma, Barjesh Chander, Lal, Bikrant Bihari, Eapen, C. E., Yaghi, Cesar, Kedarisetty, Chandan Kumar, Kim, Chang Wook, Panackel, Charles, Yu, Chen, Kalal, Chetan R., Bihari, Chhagan, Huang, Chien Hao, Vasishtha, Chitranshu, Jansen, Christian, Strassburg, Christian, Lin, Chun Yen, Karvellas, Constantine J., Lesmana, Cosmas Rinaldi Adithya, Philips, Cyriac Abby, Shawcross, Debbie, Kapoor, Dharmesh, Agrawal, Dhiraj, Payawal, Diana Alcantara, Praharaj, Dibya Lochan, Jothimani, Dinesh, Song, Do Seon, Kim, Dong Joon, Kim, Dong-Sik, Zhongping, Duan, Karim, Fazal, Durand, Francois, Shiha, Gamal E., D’Amico, Gennaro, Lau, George K., Pati, Girish Kumar, Narro, Graciela Elia Castro, Lee, Guan-Huei, Adali, Gupse, Dhakal, Guru Prasad, Szabo, Gyongyi, Lin, H. C., Li, Hai, Nair, Hari Kumar, Devarbhavi, Harshad, Tevethia, Harshvardhan, Ghazinian, Hasmik, Ilango, Hemamala, Yu, Hong Ling, Hasan, Irsan, Fernandez, J., George, Jacob, Behari, Jaideep, Fung, James, Bajaj, Jasmohan, Benjamin, Jaya, Lai, Jennifer C., Jia, Jidong, Hu, Jin Hua, Chen, Jin Jun, Hou, Jin Lin, Yang, Jin Mo, Chang, Johannes, Trebicka, Jonel, Kalf, Jörg C., Sollano, Jose D., Varghese, Joy, Arab, Juan Pablo, Li, Jun, Reddy, K. Rajender, Raja, Kaiser, Panda, Kalpana, Kajal, Kamal, Kumar, Karan, Madan, Kaushal, Kalista, Kemal Fariz, Thanapirom, Kessarin, Win, Khin Maung, Suk, Ki Tae, Devadas, Krishnadas, Lesmana, Laurentius A., Kamani, Lubna, Premkumar, Madhumita, Niriella, Madunil A., Al Mahtab, Mamun, Yuen, Man Fung, Sayed, Manal HEl, Alla, Manasa, Wadhawan, Manav, Sharma, Manoj Kumar, Sahu, Manoj, Prasad, Manya, Muthiah, Mark Dhinesh, Schulz, Martin, Bajpai, Meenu, Reddy, Mettu Srinivas, Praktiknjo, Michael, Yu, Ming Lung, Prasad, Mithra, Sharma, Mithun, Elbasiony, Mohamed, Eslam, Mohammed, Azam, Mohd. Golam, Rela, Mohd., Desai, Moreshwar S., Vij, Mukul, Mahmud, Nadim, Choudhary, Narendra Singh, Marannan, Navin Kumar, Ormeci, Necati, Saraf, Neeraj, Verma, Nipun, Nakayama, Nobuaki, Kawada, Norifumi, Oidov Baatarkhuu, Goyal, Omesh, Yokosuka, Osamu, Rao, P. N., Angeli, Paolo, Parikh, Pathik, Kamath, Patrick S., Thuluvath, Paul J., Lingohr, Philipp, Ranjan, Piyush, Bhangui, Prashant, Rathi, Pravin, Sakhuja, Puja, Puri, Puneet, Ning, Qin, Dhiman, R. K., Kumar, Rahul, Vijayaraghavan, Rajan, Khanna, Rajeev, Maiwall, Rakhi, Mohanka, Ravi, Moreau, Richard, Gani, Rino Alvani, Loomba, Rohit, Mehtani, Rohit, Rajaram, Ruveena Bhavani, Hamid, S. S., Palnitkar, Sachin, Lal, Sadhna, Biswas, Sagnik, Chirapongsathorn, Sakkarin, Agarwal, Samagra, Sachdeva, Sanjeev, Saigal, Sanjiv, Kumar, Santhosh E., Violeta, Sargsyan, Singh, Satender Pal, Mochida, Satoshi, Mukewar, Saurabh, Alam, Seema, Lim, Seng Gee, Alam, Shahinul, Shalimar, Venishetty, Shantan, Sundaram, Shikha S., Shetty, Shiran, Bhatia, Shobna, Singh, Shweta A., Kottilil, Shyam, Strasser, Simone, Shasthry, S. M., Maung, Soe Thiha, Tan, Soek Siam, Treeprasertsuk, Sombat, Asthana, Sonal, Manekeller, Steffen, Gupta, Subhash, Acharya, Subrat Kumar, K.C., Sudhamshu, Maharshi, Sudhir, Asrani, Sumeet, Dadhich, Sunil, Taneja, Sunil, Giri, Suprabhat, Singh, Surender, Chen, Tao, Gupta, Tarana, Kanda, Tatsuo, Tanwandee, Tawesak, Piratvishuth, Teerha, Spengler, Ulrich, Prasad, V. G. Mohan, Midha, Vandana, Rakhmetova, Venera, Arroyo, Vicente, Sood, Vikrant, BR, Vinay Kumar, Wong, Vincent Wai-Sun, Pamecha, Viniyendra, Singh, Virendra, Dayal, Vishwa Mohan, Saraswat, Vivek A., Kim, WRay, Jafri, Wasim, Gu, Wenyi, Jun, Wong Yu, Qi, Xiaolong, Chawla, Yogesh K., Kim, Yoon Jun, Shi, Yu, Abbas, Zaigham, Kumar, Guresh, Shiina, Shuichiro, Wei, Lai, Omata, Masao, and Sarin, Shiv Kumar

Published
2025
Full Text
View/download PDF

18. A Systematic Review on Blockchain Technology

Author

Madan, Kapil, Vij, Dinesh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Khurana, Meenu, editor, Thakur, Abhishek, editor, Kantha, Praveen, editor, Shieh, Chin-Shiuh, editor, and Shukla, Rajesh K., editor

Published
2025
Full Text
View/download PDF

19. Experimental Study to Analyze the Zonal Financial Independence of Women Using Fuzzy Logic

Author

Gupta, Prisha, Aggarwal, Yogesh, Vij, Sonakshi, Agarwal, Divya, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, Jaiswal, Ajay, editor, and Kumar, Prabhat, editor

Published
2025
Full Text
View/download PDF

20. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author

Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. R., Grimstad, Jordan, Dai, Andrew, Douglas, Sholto, Sinha, Rishika, Yadav, Vikas, Chen, Xi, Gribovskaya, Elena, Austin, Jacob, Zhao, Jeffrey, Patel, Kaushal, Komarek, Paul, Austin, Sophia, Borgeaud, Sebastian, Friso, Linda, Goyal, Abhimanyu, Caine, Ben, Cao, Kris, Chung, Da-Woon, Lamm, Matthew, Barth-Maron, Gabe, Kagohara, Thais, Olszewska, Kate, Chen, Mia, Shivakumar, Kaushik, Agarwal, Rishabh, Godhia, Harshal, Rajwar, Ravi, Snaider, Javier, Dotiwalla, Xerxes, Liu, Yuan, Barua, Aditya, Ungureanu, Victor, Zhang, Yuan, Batsaikhan, Bat-Orgil, Wirth, Mateo, Qin, James, Danihelka, Ivo, Doshi, Tulsee, Chadwick, Martin, Chen, Jilin, Jain, Sanil, Le, Quoc, Kar, Arjun, Gurumurthy, Madhu, Li, Cheng, Sang, Ruoxin, Liu, Fangyu, Lamprou, Lampros, Munoz, Rich, Lintz, Nathan, Mehta, Harsh, Howard, Heidi, Reynolds, Malcolm, Aroyo, Lora, Wang, Quan, Blanco, Lorenzo, Cassirer, Albin, Griffith, Jordan, Das, Dipanjan, Lee, Stephan, Sygnowski, Jakub, Fisher, Zach, Besley, James, Powell, Richard, Ahmed, Zafarali, Paulus, Dominik, Reitter, David, Borsos, Zalan, Joshi, Rishabh, Pope, Aedan, Hand, Steven, Selo, Vittorio, Jain, Vihan, Sethi, Nikhil, Goel, Megha, Makino, Takaki, May, Rhys, Yang, Zhen, Schalkwyk, Johan, Butterfield, Christina, Hauth, Anja, Goldin, Alex, Hawkins, Will, Senter, Evan, Brin, Sergey, Woodman, Oliver, Ritter, Marvin, Noland, Eric, Giang, Minh, Bolina, Vijay, Lee, Lisa, Blyth, Tim, Mackinnon, Ian, Reid, Machel, Sarvana, Obaid, Silver, David, Chen, Alexander, Wang, Lily, Maggiore, Loren, Chang, Oscar, Attaluri, Nithya, Thornton, Gregory, Chiu, Chung-Cheng, Bunyan, Oskar, Levine, Nir, Chung, Timothy, Eltyshev, Evgenii, Si, Xiance, Lillicrap, Timothy, Brady, Demetra, Aggarwal, Vaibhav, Wu, Boxi, Xu, Yuanzhong, McIlroy, Ross, Badola, Kartikeya, Sandhu, Paramjit, Moreira, Erica, Stokowiec, Wojciech, Hemsley, Ross, Li, Dong, Tudor, Alex, Shyam, Pranav, Rahimtoroghi, Elahe, Haykal, Salem, Sprechmann, Pablo, Zhou, Xiang, Mincu, Diana, Li, Yujia, Addanki, Ravi, Krishna, Kalpesh, Wu, Xiao, Frechette, Alexandre, Eyal, Matan, Dafoe, Allan, Lacey, Dave, Whang, Jay, Avrahami, Thi, Zhang, Ye, Taropa, Emanuel, Lin, Hanzhao, Toyama, Daniel, Rutherford, Eliza, Sano, Motoki, Choe, HyunJeong, Tomala, Alex, Safranek-Shrader, Chalence, Kassner, Nora, Pajarskas, Mantas, Harvey, Matt, Sechrist, Sean, Fortunato, Meire, Lyu, Christina, Elsayed, Gamaleldin, Kuang, Chenkai, Lottes, James, Chu, Eric, Jia, Chao, Chen, Chih-Wei, Humphreys, Peter, Baumli, Kate, Tao, Connie, Samuel, Rajkumar, Santos, Cicero Nogueira dos, Andreassen, Anders, Rakićević, Nemanja, Grewe, Dominik, Kumar, Aviral, Winkler, Stephanie, Caton, Jonathan, Brock, Andrew, Dalmia, Sid, Sheahan, Hannah, Barr, Iain, Miao, Yingjie, Natsev, Paul, Devlin, Jacob, Behbahani, Feryal, Prost, Flavien, Sun, Yanhua, Myaskovsky, Artiom, Pillai, Thanumalayan Sankaranarayana, Hurt, Dan, Lazaridou, Angeliki, Xiong, Xi, Zheng, Ce, Pardo, Fabio, Li, Xiaowei, Horgan, Dan, Stanton, Joe, Ambar, Moran, Xia, Fei, Lince, Alejandro, Wang, Mingqiu, Mustafa, Basil, Webson, Albert, Lee, Hyo, Anil, Rohan, Wicke, Martin, Dozat, Timothy, Sinha, Abhishek, Piqueras, Enrique, Dabir, Elahe, Upadhyay, Shyam, Boral, Anudhyan, Hendricks, Lisa Anne, Fry, Corey, Djolonga, Josip, Su, Yi, Walker, Jake, Labanowski, Jane, Huang, Ronny, Misra, Vedant, Chen, Jeremy, Skerry-Ryan, RJ, Singh, Avi, Rijhwani, Shruti, Yu, Dian, Castro-Ros, Alex, Changpinyo, Beer, Datta, Romina, Bagri, Sumit, Hrafnkelsson, Arnar Mar, Maggioni, Marcello, Zheng, Daniel, Sulsky, Yury, Hou, Shaobo, Paine, Tom Le, Yang, Antoine, Riesa, Jason, Rogozinska, Dominika, Marcus, Dror, Badawy, Dalia El, Zhang, Qiao, Wang, Luyu, Miller, Helen, Greer, Jeremy, Sjos, Lars Lowe, Nova, Azade, Zen, Heiga, Chaabouni, Rahma, Rosca, Mihaela, Jiang, Jiepu, Chen, Charlie, Liu, Ruibo, Sainath, Tara, Krikun, Maxim, Polozov, Alex, Lespiau, Jean-Baptiste, Newlan, Josh, Cankara, Zeyncep, Kwak, Soo, Xu, Yunhan, Chen, Phil, Coenen, Andy, Meyer, Clemens, Tsihlas, Katerina, Ma, Ada, Gottweis, Juraj, Xing, Jinwei, Gu, Chenjie, Miao, Jin, Frank, Christian, Cankara, Zeynep, Ganapathy, Sanjay, Dasgupta, Ishita, Hughes-Fitt, Steph, Chen, Heng, Reid, David, Rong, Keran, Fan, Hongmin, van Amersfoort, Joost, Zhuang, Vincent, Cohen, Aaron, Gu, Shixiang Shane, Mohananey, Anhad, Ilic, Anastasija, Tobin, Taylor, Wieting, John, Bortsova, Anna, Thacker, Phoebe, Wang, Emma, Caveness, Emily, Chiu, Justin, Sezener, Eren, Kaskasoli, Alex, Baker, Steven, Millican, Katie, Elhawaty, Mohamed, Aisopos, Kostas, Lebsack, Carl, Byrd, Nathan, Dai, Hanjun, Jia, Wenhao, Wiethoff, Matthew, Davoodi, Elnaz, Weston, Albert, Yagati, Lakshman, Ahuja, Arun, Gao, Isabel, Pundak, Golan, Zhang, Susan, Azzam, Michael, Sim, Khe Chai, Caelles, Sergi, Keeling, James, Sharma, Abhanshu, Swing, Andy, Li, YaGuang, Liu, Chenxi, Bostock, Carrie Grimes, Bansal, Yamini, Nado, Zachary, Anand, Ankesh, Lipschultz, Josh, Karmarkar, Abhijit, Proleev, Lev, Ittycheriah, Abe, Yeganeh, Soheil Hassas, Polovets, George, Faust, Aleksandra, Sun, Jiao, Rrustemi, Alban, Li, Pen, Shivanna, Rakesh, Liu, Jeremiah, Welty, Chris, Lebron, Federico, Baddepudi, Anirudh, Krause, Sebastian, Parisotto, Emilio, Soricut, Radu, Xu, Zheng, Bloxwich, Dawn, Johnson, Melvin, Neyshabur, Behnam, Mao-Jones, Justin, Wang, Renshen, Ramasesh, Vinay, Abbas, Zaheer, Guez, Arthur, Segal, Constant, Nguyen, Duc Dung, Svensson, James, Hou, Le, York, Sarah, Milan, Kieran, Bridgers, Sophie, Gworek, Wiktor, Tagliasacchi, Marco, Lee-Thorp, James, Chang, Michael, Guseynov, Alexey, Hartman, Ale Jakse, Kwong, Michael, Zhao, Ruizhe, Kashem, Sheleem, Cole, Elizabeth, Miech, Antoine, Tanburn, Richard, Phuong, Mary, Pavetic, Filip, Cevey, Sebastien, Comanescu, Ramona, Ives, Richard, Yang, Sherry, Du, Cosmo, Li, Bo, Zhang, Zizhao, Iinuma, Mariko, Hu, Clara Huiyi, Roy, Aurko, Bijwadia, Shaan, Zhu, Zhenkai, Martins, Danilo, Saputro, Rachel, Gergely, Anita, Zheng, Steven, Jia, Dawei, Antonoglou, Ioannis, Sadovsky, Adam, Gu, Shane, Bi, Yingying, Andreev, Alek, Samangooei, Sina, Khan, Mina, Kocisky, Tomas, Filos, Angelos, Kumar, Chintu, Bishop, Colton, Yu, Adams, Hodkinson, Sarah, Mittal, Sid, Shah, Premal, Moufarek, Alexandre, Cheng, Yong, Bloniarz, Adam, Lee, Jaehoon, Pejman, Pedram, Michel, Paul, Spencer, Stephen, Feinberg, Vladimir, Xiong, Xuehan, Savinov, Nikolay, Smith, Charlotte, Shakeri, Siamak, Tran, Dustin, Chesus, Mary, Bohnet, Bernd, Tucker, George, von Glehn, Tamara, Muir, Carrie, Mao, Yiran, Kazawa, Hideto, Slone, Ambrose, Soparkar, Kedar, Shrivastava, Disha, Cobon-Kerr, James, Sharman, Michael, Pavagadhi, Jay, Araya, Carlos, Misiunas, Karolis, Ghelani, Nimesh, Laskin, Michael, Barker, David, Li, Qiujia, Briukhov, Anton, Houlsby, Neil, Glaese, Mia, Lakshminarayanan, Balaji, Schucher, Nathan, Tang, Yunhao, Collins, Eli, Lim, Hyeontaek, Feng, Fangxiaoyu, Recasens, Adria, Lai, Guangda, Magni, Alberto, De Cao, Nicola, Siddhant, Aditya, Ashwood, Zoe, Orbay, Jordi, Dehghani, Mostafa, Brennan, Jenny, He, Yifan, Xu, Kelvin, Gao, Yang, Saroufim, Carl, Molloy, James, Wu, Xinyi, Arnold, Seb, Chang, Solomon, Schrittwieser, Julian, Buchatskaya, Elena, Radpour, Soroush, Polacek, Martin, Giordano, Skye, Bapna, Ankur, Tokumine, Simon, Hellendoorn, Vincent, Sottiaux, Thibault, Cogan, Sarah, Severyn, Aliaksei, Saleh, Mohammad, Thakoor, Shantanu, Shefey, Laurent, Qiao, Siyuan, Gaba, Meenu, Chang, Shuo-yiin, Swanson, Craig, Zhang, Biao, Lee, Benjamin, Rubenstein, Paul Kishan, Song, Gan, Kwiatkowski, Tom, Koop, Anna, Kannan, Ajay, Kao, David, Schuh, Parker, Stjerngren, Axel, Ghiasi, Golnaz, Gibson, Gena, Vilnis, Luke, Yuan, Ye, Ferreira, Felipe Tiengo, Kamath, Aishwarya, Klimenko, Ted, Franko, Ken, Xiao, Kefan, Bhattacharya, Indro, Patel, Miteyan, Wang, Rui, Morris, Alex, Strudel, Robin, Sharma, Vivek, Choy, Peter, Hashemi, Sayed Hadi, Landon, Jessica, Finkelstein, Mara, Jhakra, Priya, Frye, Justin, Barnes, Megan, Mauger, Matthew, Daun, Dennis, Baatarsukh, Khuslen, Tung, Matthew, Farhan, Wael, Michalewski, Henryk, Viola, Fabio, Quitry, Felix de Chaumont, Lan, Charline Le, Hudson, Tom, Wang, Qingze, Fischer, Felix, Zheng, Ivy, White, Elspeth, Dragan, Anca, Alayrac, Jean-baptiste, Ni, Eric, Pritzel, Alexander, Iwanicki, Adam, Isard, Michael, Bulanova, Anna, Zilka, Lukas, Dyer, Ethan, Sachan, Devendra, Srinivasan, Srivatsan, Muckenhirn, Hannah, Cai, Honglong, Mandhane, Amol, Tariq, Mukarram, Rae, Jack W., Wang, Gary, Ayoub, Kareem, FitzGerald, Nicholas, Zhao, Yao, Han, Woohyun, Alberti, Chris, Garrette, Dan, Krishnakumar, Kashyap, Gimenez, Mai, Levskaya, Anselm, Sohn, Daniel, Matak, Josip, Iturrate, Inaki, Chang, Michael B., Xiang, Jackie, Cao, Yuan, Ranka, Nishant, Brown, Geoff, Hutter, Adrian, Mirrokni, Vahab, Chen, Nanxin, Yao, Kaisheng, Egyed, Zoltan, Galilee, Francois, Liechty, Tyler, Kallakuri, Praveen, Palmer, Evan, Ghemawat, Sanjay, Liu, Jasmine, Tao, David, Thornton, Chloe, Green, Tim, Jasarevic, Mimi, Lin, Sharon, Cotruta, Victor, Tan, Yi-Xuan, Fiedel, Noah, Yu, Hongkun, Chi, Ed, Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Munkhdalai, Tsendsuren, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Perz, Bartek, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeff, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.

Published
2024

23. IL-10R inhibition reprograms tumor-associated macrophages and reverses drug resistance in multiple myeloma

Author

Sun, Jennifer, Corradini, Stefan, Azab, Feda, Shokeen, Monica, Muz, Barbara, Miari, Katerina E., Maksimos, Mina, Diedrich, Camila, Asare, Obed, Alhallak, Kinan, Park, Chaelee, Lubben, Berit, Chen, Yixuan, Adebayo, Ola, Bash, Hannah, Kelley, Sarah, Fiala, Mark, Bender, Diane E., Zhou, Haibin, Wang, Shaomeng, Vij, Ravi, Williams, Mark T. S., and Azab, Abdel Kareem

Published
2024
Full Text
View/download PDF

32. Interplay of plasmonics and strain for Hexagonal Boron Nitride emission engineering

Author

Singh, Anuj Kumar, Utkarsh, Tieben, Pablo, Mandal, Kishor Kumar, Kumar, Brijesh, Vij, Rishabh, Majumder, Amrita, Shyam, Ikshvaku, Kumar, Shagun, Watanabe, Kenji, Taniguchi, Takashi, Achanta, Venu Gopal, Schell, Andreas, and Kumar, Anshuman

Subjects
Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

In the realm of quantum information and sensing, there has been substantial interest in the single-photon emission associated with defects in hexagonal boron nitride (hBN). With the goal of producing deterministic emission centers, in this work, we present a platform for engineering emission in hBN integrated with gold truncated nanocone structures. Our findings highlights that, the activation of emission is due to the truncated gold nanocones. Furthermore, we measure the quantum characteristics of this emission and find that while our system demonstrates support for single-photon emission, the origin of this emission remains ambiguous. Specifically, it is unclear whether the emission arises from defects generated by the induced strain or from alternative defect mechanisms. This uncertainty stems from the fluorescence properties inherent to gold, complicating our definitive attribution of the quantum emission source. To provide a rigorous theoretical foundation, we elucidate the effects of strain via the Kirchhoff-Love theory. Additionally, the enhancements observed due to plasmonic effects are comprehensively explained through the resolution of Maxwell's equations. This study will be useful for the development of deterministic and tunable single photonic sources in two dimensional materials and their integration with plasmonic platforms.

Published
2024

33. Emission engineering in monolithically integrated silicon nitride microring resonators

Author

Mandal, Kishor Kumar, Singh, Anuj Kumar, Kumar, Brijesh, Shah, Amit P., Vij, Rishabh, Majumder, Amrita, Khunte, Janhavi Jayawant, Achanta, Venu Gopal, and Kumar, Anshuman

Subjects
Condensed Matter - Materials Science, Physics - Optics
Abstract

Monolithic integration of solid-state color centers with photonic elements of the same material is a promising approach to overcome the constraints of fabrication complexity and coupling losses in traditional hybrid integration approaches. A wide band-gap, low-loss silicon nitride (SiN) platform is a mature technology, having CMOS compatibility, widely used in hybrid integrated photonics and optoelectronics. However, it has been shown that certain growth conditions enable the SiN material to host color centers, whose origin is currently under investigation. In this work, we have engineered a novel technique for the efficient coupling of these intrinsic emitters into the whispering gallery modes (WGMs) of the SiN microring cavity -- which has not been explored previously. We have engineered a subwavelength-sized notch into the rim of the SiN microring structure, to optimize the collection efficiency of the cavity-coupled enhanced photoluminescence (PL) spectra at room temperature. The platform presented in this work will enable the development of monolithic integration of color centers with nanophotonic elements for application to quantum photonic technologies.

Published
2024

37. Genomic characterization of cervical lymph node metastases in papillary thyroid carcinoma following the Chornobyl accident

Author

Morton, Lindsay M., Lee, Olivia W., Karyadi, Danielle M., Bogdanova, Tetiana I., Stewart, Chip, Hartley, Stephen W., Breeze, Charles E., Schonfeld, Sara J., Cahoon, Elizabeth K., Drozdovitch, Vladimir, Masiuk, Sergii, Chepurny, Mykola, Zurnadzhy, Liudmyla Yu, Dai, Jieqiong, Krznaric, Marko, Yeager, Meredith, Hutchinson, Amy, Hicks, Belynda D., Dagnall, Casey L., Steinberg, Mia K., Jones, Kristine, Jain, Komal, Jordan, Ben, Machiela, Mitchell J., Dawson, Eric T., Vij, Vibha, Gastier-Foster, Julie M., Bowen, Jay, Mabuchi, Kiyohiko, Hatch, Maureen, Berrington de Gonzalez, Amy, Getz, Gad, Tronko, Mykola D., Thomas, Gerry A., and Chanock, Stephen J.

Published
2024
Full Text
View/download PDF

38. Understanding how junction resistances impact the conduction mechanism in nano-networks

Author

Gabbett, Cian, Kelly, Adam G., Coleman, Emmet, Doolan, Luke, Carey, Tian, Synnatschke, Kevin, Liu, Shixin, Dawson, Anthony, O’Suilleabhain, Domhnall, Munuera, Jose, Caffrey, Eoin, Boland, John B., Sofer, Zdeněk, Ghosh, Goutam, Kinge, Sachin, Siebbeles, Laurens D. A., Yadav, Neelam, Vij, Jagdish K., Aslam, Muhammad Awais, Matkovic, Aleksandar, and Coleman, Jonathan N.

Published
2024
Full Text
View/download PDF

39. Cavity enhanced emission from a silicon T center

Author

Islam, Fariba, Lee, Chang-Min, Harper, Samuel, Rahaman, Mohammad Habibur, Zhao, Yuqi, Vij, Neelesh Kumar, and Waks, Edo

Subjects
Physics - Optics, Quantum Physics
Abstract

Silicon T centers present the promising possibility to generate optically active spin qubits in an all-silicon device. However, these color centers exhibit long excited state lifetimes and a low Debye-Waller factor, making them dim emitters with low efficiency into the zero-phonon line. Nanophotonic cavities can solve this problem by enhancing radiative emission into the zero-phonon line through the Purcell effect. In this work we demonstrate cavity-enhanced emission from a single T center in a nanophotonic cavity. We achieve a two-orders of magnitude increase in brightness of the zero-phonon line relative to waveguide-coupled emitters, a 23% collection efficiency from emitter to fiber, and an overall emission efficiency into the zero-phonon line of 63.4%. We also observe a lifetime enhancement of 5, corresponding to a Purcell factor exceeding 18 when correcting for the emission to the phonon sideband. These results pave the way towards efficient spin-photon interfaces in silicon photonics., Comment: References updated

Published
2023
Full Text
View/download PDF

40. Combination clomiphene citrate and anastrozole duotherapy improves semen parameters in a multi-institutional, retrospective cohort of infertile men.

Author

Osadchiy, Vadim, Munoz-Lopez, Carlos, Jiang, Tommy, Naelitz, Bryan, Parekh, Neel, Vij, Sarah, Mills, Jesse, Lundy, Scott, and Eleswarapu, Sriram

Subjects
Clomiphene, anastrozole, idiopathic infertility, semen analysis parameters (SA parameters), total motile sperm count (TMSC)
Abstract

In men with impaired semen parameters, empiric medical therapies such as clomiphene citrate, a selective estrogen receptor modulator (SERM), and anastrozole, a selective aromatase inhibitor, are often employed. The effects of jointly administering these agents on semen parameters are not well understood. Here, we describe the findings of our multi-center, retrospective cohort study of men with idiopathic primary or secondary infertility. Twenty-one men were treated with combination therapy (anastrozole and clomiphene) and 69 men were treated with monotherapy (anastrozole). Patients with pre-treatment normozoospermia and recent or current exogenous testosterone therapy were excluded. Baseline and post-treatment semen and sex hormone parameters were compared among groups. The median follow-up duration was 91 days [interquartile range (IQR), 64-117 days]. Following treatment, 43% of men in the combination therapy group demonstrated normozoospermia, compared to 25% in the monotherapy group. Furthermore, men in the combined group demonstrated marked improvements in total motile sperm count (TMSC) [11.3 vs. 2.1 million (M), P=0.03]. There were no significant differences in hormone levels among the two groups following treatment. Combination therapy with clomiphene citrate and anastrozole was associated with modest benefits in post-treatment semen parameters, when compared to anastrozole monotherapy. These benefits may contribute to improvements in pregnancy outcomes with less invasive assisted reproductive technologies, such as intrauterine insemination (IUI). Future investigations with larger sample sizes and prospective study designs are necessary.

Published
2024

42. Management of a Portobiliary Fistula and Obstructive Biliopathy in a Split Liver Graft Transplant Recipient Posthepaticojejunostomy with Portal Stent Graft

Author

Saurabh Kumar, Apoorva Batra, Vaibhaw Kumar, and Vivek Vij

Subjects
portobiliary fistula, liver transplant, hepaticojejunostomy, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Biliary complications following liver transplantations, in the form of bile leak and bile duct strictures, are well recognized. Portobiliary fistulas in the transplant setting are rare, but may cause potentially life-threatening complications. The presented case shows the successful treatment of a hilar portobiliary fistula in a transplanted liver posthepaticojejunostomy with portal vein stent graft followed by biliary drainage with percutaneous hepaticojejunostomy stricture dilatation.

Published
2024
Full Text
View/download PDF

46. The Deafening Silence of Male Infertility

Author

Nam, Catherine S, Campbell, Kevin J, Acquati, Chiara, Bole, Raevti, Adler, Ava, Collins, David J, Collins, Erica, Samplaski, Mary, Anderson-Bialis, Jake, Andino, Juan J, Asafu-Adjei, Denise, Gaskins, Audrey J, Bortoletto, Pietro, Vij, Sarah C, Orwig, Kyle E, and Lundy, Scott D

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Infertility, Contraception/Reproduction, Reproductive health and childbirth, Clinical Sciences, Urology & Nephrology, Clinical sciences
Published
2023

47. Hibernate Container: A Deflated Container Mode for Fast Startup and High-density Deployment in Serverless Computing

Author

Sun, Yulin, Vij, Deepak, Li, Fenge, Guo, Wenjian, and Xiong, Ying

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Serverless computing is a popular cloud computing paradigm, which requires low response latency to handle on-demand user requests. There are two prominent techniques employed for reducing the response latency: keep fully initialized containers alive (Warm Container) or reduce the new container startup (cold start) latency. This paper presents the 3rd container startup mode: Hibernate Container, which starts faster than the cold start container mode and consumes less memory than the Warm Container mode. Hibernate Container is essentially a "deflated" Warm Container. Its application memory is swapped out to disk, the freed memory is reclaimed and file based mmap memory is cleaned-up. The Hibernate Container's deflated memory is inflated in response to user requests. As Hibernate Container's application is fully initialized, its response latency is less than the cold start mode; and as the application memory is deflated, its memory consumption is less than the Warm Container mode. Additionally, when a Hibernate Container is "woken up" to process a request, the Woken-up Container has similar response latency to Warm Container but less memory consumption because not all the deflated memory needs to be inflated. We implemented the Hibernate technique as part of the open source Quark secure container runtime project and our test demonstrated that Hibernate Container consumes about 7\% to 25\% of the Warm Container memory. All of this results in a higher deployment density, lower latency and appreciable improvements in the overall system performance.

Published
2023

48. Nanobiotechnology in Personalized Oncology

Author

Kumar, Umesh, primary, Kumari, Mansi, additional, Sahu, Bhupendra, additional, Vij, Daanish, additional, Virmani, Lakshay, additional, Thakur, Neelam, additional, and Chatterji, Tanushri, additional

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results