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Automated Machine Learning (AutoML) has simplified complex ML processes such as data pre-processing, model selection, and hyper-parameter searching. However, traditional AutoML frameworks focus solely on discriminative tasks, often falling short in tackling AutoML for generative models. Additionally, these frameworks lack interpretability and user engagement during the training process, primarily due to the absence of human-centered design. It leads to a lack of transparency in final decision-making and limited user control, potentially reducing trust and adoption of AutoML methods. To address these limitations, we introduce UniAutoML, a human-centered AutoML framework that leverages Large Language Models (LLMs) to unify AutoML for both discriminative (e.g., Transformers and CNNs for classification or regression tasks) and generative tasks (e.g., fine-tuning diffusion models or LLMs). The human-centered design of UniAutoML innovatively features a conversational user interface (CUI) that facilitates natural language interactions, providing users with real-time guidance, feedback, and progress updates for better interpretability. This design enhances transparency and user control throughout the AutoML training process, allowing users to seamlessly break down or modify the model being trained. To mitigate potential risks associated with LLM generated content, UniAutoML incorporates a safety guardline that filters inputs and censors outputs. We evaluated UniAutoML's performance and usability through experiments on eight diverse datasets and user studies involving 25 participants, demonstrating that UniAutoML not only enhances performance but also improves user control and trust. Our human-centered design bridges the gap between AutoML capabilities and user understanding, making ML more accessible to a broader audience.

Audio-driven 3D facial animation has made immersive progress both in research and application developments. The newest approaches focus on Transformer-based methods and diffusion-based methods, however, there is still gap in the vividness and emotional expression between the generated animation and real human face. To tackle this limitation, we propose 3DFacePolicy, a diffusion policy model for 3D facial animation prediction. This method generates variable and realistic human facial movements by predicting the 3D vertex trajectory on the 3D facial template with diffusion policy instead of facial generation for every frame. It takes audio and vertex states as observations to predict the vertex trajectory and imitate real human facial expressions, which keeps the continuous and natural flow of human emotions. The experiments show that our approach is effective in variable and dynamic facial motion synthesizing.

Emotion recognition can enhance humanized machine responses to user commands, while voiceprint-based perception systems can be easily integrated into commonly used devices like smartphones and stereos. Despite having the largest number of speakers, there is a noticeable absence of high-quality corpus datasets for emotion recognition using Chinese voiceprints. Hence, this paper introduces the VCEMO dataset to address this deficiency. The proposed dataset is constructed from everyday conversations and comprises over 100 users and 7,747 textual samples. Furthermore, this paper proposes a multimodal-based model as a benchmark, which effectively fuses speech, text, and external knowledge using a co-attention structure. The system employs contrastive learning-based regulation for the uneven distribution of the dataset and the diversity of emotional expressions. The experiments demonstrate the significant improvement of the proposed model over SOTA on the VCEMO and IEMOCAP datasets. Code and dataset will be released for research., Comment: 12 pages, 4 figures

Multimodal Large Language Models (MLLMs) have demonstrated remarkable multimodal emotion recognition capabilities, integrating multimodal cues from visual, acoustic, and linguistic contexts in the video to recognize human emotional states. However, existing methods ignore capturing local facial features of temporal dynamics of micro-expressions and do not leverage the contextual dependencies of the utterance-aware temporal segments in the video, thereby limiting their expected effectiveness to a certain extent. In this work, we propose MicroEmo, a time-sensitive MLLM aimed at directing attention to the local facial micro-expression dynamics and the contextual dependencies of utterance-aware video clips. Our model incorporates two key architectural contributions: (1) a global-local attention visual encoder that integrates global frame-level timestamp-bound image features with local facial features of temporal dynamics of micro-expressions; (2) an utterance-aware video Q-Former that captures multi-scale and contextual dependencies by generating visual token sequences for each utterance segment and for the entire video then combining them. Preliminary qualitative experiments demonstrate that in a new Explainable Multimodal Emotion Recognition (EMER) task that exploits multi-modal and multi-faceted clues to predict emotions in an open-vocabulary (OV) manner, MicroEmo demonstrates its effectiveness compared with the latest methods.

High-fidelity detection of quantum states is indispensable for implementing quantum error correction, a prerequisite for fault-tolerant quantum computation. For promising trapped ion qubits, however, the detection fidelity is inherently limited by state leakage. Here, we propose an efficient approach to enhance the fidelity of detecting $^{171} \mathrm{Yb}^+$ qubits through $^2D_{3/2}$ state shelving techniques. Leveraging selective shelving and state-dependent fluorescence, we mitigate the impact of state leakage and experimentally realize a fidelity of 99.88(2)%, while over 99.99% fidelity is predicted by utilizing state-of-the-art hardwares. Meanwhile, we demonstrate the feasibility of mid-circuit measurements, a crucial step for recent implementations of quantum error correction, by mapping the hyperfine qubit to metastable levels. Our research provides an essential component for realizing fault-tolerant quantum information processing with trapped-ion systems in the near future., Comment: 8 pages, 6 figures

We present 206 unpublished optical spectra of 104 type II supernovae obtained by the Xinglong 2.16m telescope and Lijiang 2.4m telescope during the period from 2011 to 2018, spanning the phases from about 1 to 200 days after the SN explosion. The spectral line identifications, evolution of line velocities and pseudo equivalent widths, as well as correlations between some important spectral parameters are presented. Our sample displays a large range in expansion velocities. For instance, the Fe~{\sc ii} $5169$ velocities measured from spectra at $t\sim 50$ days after the explosion vary from ${\rm 2000\ km\ s^{-1}}$ to ${\rm 5500\ km\ s^{-1}}$, with an average value of ${\rm 3872 \pm 949\ km\ s^{-1}}$. Power-law functions can be used to fit the velocity evolution, with the power-law exponent quantifying the velocity decline rate. We found an anticorrelation existing between H$\beta$ velocity at mid-plateau phase and its velocity decay exponent, SNe II with higher velocities tending to have smaller velocity decay rate. Moreover, we noticed that the velocity decay rate inferred from the Balmer lines (i.e., H$\alpha$ and H$\beta$) have moderate correlations with the ratio of absorption to emission for H$\alpha$ (a/e). In our sample, two objects show possibly flash-ionized features at early phases. Besides, we noticed that multiple high-velocity components may exist on the blue side of hydrogen lines of SN 2013ab, possibly suggesting that these features arise from complex line forming region. All our spectra can be found in WISeREP and Zenodo.

We present the discovery of three pulsars in the Globular Cluster (GC) M15 (NGC 7078) by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). PSR J2129+1210J (M15J) is a millisecond pulsar with a spin period of 11.84 ms and a dispersion measure of 66.68 pc cm-3. Both PSR J2129+1210K and L (M15K and L) are long-period pulsars with spin periods of 1928 ms and 3961 ms, respectively. M15L is the GC pulsar with the longest spin period known. The timing solutions of M15A to M15H are updated. As predicted by Ridolfi et al.(2018), the flux density of M15C keeps decreasing and the latest detection in our dataset was on December 20th, 2022. We have also detected M15I's signal for the first time since its discovery. Current timing suggests that it is an isolated pulsar., Comment: 13 pages, 4 figures, 3 tables, accepted by ApJ Letters

Millisecond pulsars can serve as effective probes to investigate the presence of Intermediate-mass Black Holes (IMBHs) within Galactic globular clusters (GCs). Based on the standard structure models for GCs, we conduct simulations to analyze the distributions of pulsar accelerations within the central region of NGC 6517. By comparing the measured accelerations of pulsars obtained from their period derivatives $\dot P$ to the simulated distribution profiles, we demonstrate that a central excess of dark mass is required to account for the measured accelerations. Our analysis, which relies on existing pulsar timing observations, is currently unable to differentiate between two possible scenarios: an IMBH precisely situated at the core of the cluster with mass $\gtrsim 9000^{+4000}_{-3000}~M_{\odot}$, or a central concentration of stellar mass dark remnants with a comparable total mass. However, with additional acceleration measurements from a few more pulsars in the cluster, it will be possible to differentiate the source of the nonluminous matter., Comment: 6 pages, 3 figures, 1 table. Accepted for publication in MNRAS

Double white dwarf systems are of great astrophysical importance in the field of gravitational wave and Type Ia supernova. While the binary fraction of CO core white dwarf is about a few percents, the extremely low mass white dwarfs are all thought to be within binary systems. In this work, we report the orbital solution of a double degenerate system: J033847.06+413424.24, an extremely low mass He core white dwarf orbiting a CO core white dwarf. With LAMOST and P200, time domain spectroscopic observations have been made and spectral atmosphere parameters are estimated to be $T_{\rm eff}\sim22500$ K and log $g\sim5.6$ dex. Combining Gaia parallax, 3D extinction, and evolution tracks, we estimate a radius of $\sim0.12$ $R_{\odot}$ and a mass of $\sim0.22$ $M_{\odot}$. With the 37 single exposure spectra, the radial velocities are measured and the orbital parameters are estimated to be $P=0.1253132(1)$ days, $K1=289\pm4$ km/s and $V_{sys}=-41\pm3$ km/s. The radial velocity based system ephemeris is also provided. The light curves from several photometric surveys show no orbital modulation. The orbital solution suggests that the invisible companion has a minimum mass of about 0.60 $M_{\odot}$ and is $\sim0.79$ $M_{\odot}$ for an inclination of $60.0^{\circ}$, indicating most probably a CO core white dwarf. The system is expected to merge in about 1 Gyr. With present period and distance ($\sim596$ pc) it can not irradiate strong enough gravitational wave for LISA. More double degenerate systems are expected to be discovered and parameterized as the LAMOST survey goes on., Comment: 12 pages, 11 figures

Using data from the Gaia Data Release 3 (Gaia DR3) and Kepler/K2, we present a catalog of 16 open clusters with ages ranging from 4 to 4000 Myr, which provides detailed information on membership, binary systems, and rotation. We assess the memberships in 5D phase space, and estimate the basic parameters of each cluster. Among the 20,160 members, there are 4,381 stars identified as binary candidates and 49 stars as blue straggler stars. The fraction of binaries vary in each cluster, and the range between 9% to 44%. We obtain the rotation periods of 5,467 members, of which 4,304 are determined in this work. To establish a benchmark for the rotation-age-color relation, we construct color-period diagrams. We find that the rotational features of binaries are similar to that of single stars, while features for binaries are more scattered in the rotation period. Moreover, the morphology of the color-period relationship is already established for Upper Scorpius at the age of 19 Myr, and some stars of varying spectral types (i.e. FG-, K-, and M-type) show different spin-down rates after the age of ~110 Myr. By incorporating the effects of stalled spin-down into our analysis, we develop an empirical rotation-age-color relation, which is valid with ages between 700 - 4000 Myr and colors corresponding to a range of 0.5 < (G_BP-G_RP)0 < 2.5 mag., Comment: 21 pages, 17 figures, accepted for publication in ApJS

Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) aims to detect fast-evolving transients in the Universe, which has led to the discovery of thousands of short-period variables and eclipsing binaries since 2020. In this paper, we present the observed properties of 125 flare stars identified by the TMTS within the first two years, with an attempt to constrain their eruption physics. As expected, most of these flares were recorded in late-type red stars with $G_{\rm BP}-G_{\rm RP}$ > 2.0 mag, however, the flares associated with bluer stars tend to be on average more energetic and have broader profiles. The peak flux (F_peak) of the flare is found to depend strongly on the equivalent duration (ED) of the energy release, i.e., $F_{{\rm peak}} \propto {\rm ED}^{0.72\pm0.04}$, which is consistent with results derived from the Kepler and Evryscope samples. This relation is likely related to the magnetic loop emission, while -- for the more popular non-thermal electron heating model -- a specific time evolution may be required to generate this relation. We notice that flares produced by hotter stars have a flatter $F_{{\rm peak}} \propto {\rm ED}$ relation compared to that from cooler stars. This is related to the statistical discrepancy in light-curve shape of flare events with different colors. In spectra from LAMOST, we find that flare stars have apparently stronger H alpha emission than inactive stars, especially at the low temperature end, suggesting that chromospheric activity plays an important role in producing flares. On the other hand, the subclass having frequent flares are found to show H alpha emission of similar strength in their spectra to that recorded with only a single flare but similar effective temperature, implying that the chromospheric activity may not be the only trigger for eruptions., Comment: 17 pages, 15 figures, 2 tables, refereed version. For associated data files, see https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/523/2193

We propose to develop a wide-field and ultra-high-precision photometric survey mission, temporarily named "Earth 2.0 (ET)". This mission is designed to measure, for the first time, the occurrence rate and the orbital distributions of Earth-sized planets. ET consists of seven 30cm telescopes, to be launched to the Earth-Sun's L2 point. Six of these are transit telescopes with a field of view of 500 square degrees. Staring in the direction that encompasses the original Kepler field for four continuous years, this monitoring will return tens of thousands of transiting planets, including the elusive Earth twins orbiting solar-type stars. The seventh telescope is a 30cm microlensing telescope that will monitor an area of 4 square degrees toward the galactic bulge. This, combined with simultaneous ground-based KMTNet observations, will measure masses for hundreds of long-period and free-floating planets. Together, the transit and the microlensing telescopes will revolutionize our understandings of terrestrial planets across a large swath of orbital distances and free space. In addition, the survey data will also facilitate studies in the fields of asteroseismology, Galactic archeology, time-domain sciences, and black holes in binaries., Comment: 116 pages,79 figures

Synchronizing a few-level quantum system is of fundamental importance to understanding synchronization in deep quantum regime. Whether a two-level system, the smallest quantum system, can be synchronized has been theoretically debated for the past several years. Here, for the first time, we demonstrate that a qubit can indeed be synchronized to an external driving signal by using a trapped-ion system. By engineering fully controllable gain and damping processes, an ion qubit is synchronized to oscillate at the same frequency as the driving signal and lock in phase. We systematically investigate the parameter regions of synchronization and observe characteristic features of the Arnold tongue. Our measurements agree remarkably well with numerical simulations based on recent theory on qubit synchronization. By synchronizing the basic unit of quantum information, our research opens up the possibility of applying quantum synchronization to large-scale quantum networks., Comment: Main: 6 pages, 4 figures and Supplemental Material: 12 pages, 7 figures

Stellar flares are characterized by sudden enhancement of electromagnetic radiation in stellar atmospheres. So far much of our understanding of stellar flares comes from photometric observations, from which plasma motions in flare regions could not be detected. From the spectroscopic data of LAMOST DR7, we have found one stellar flare that is characterized by an impulsive increase followed by a gradual decrease in the H$\alpha$ line intensity on an M4-type star, and the total energy radiated through H${\alpha}$ is estimated to be on the order of $10^{33}$ erg. The H$\alpha$ line appears to have a Voigt profile during the flare, which is likely caused by Stark pressure broadening due to the dramatic increase of electron density and/or opacity broadening due to the occurrence of strong non-thermal heating. Obvious enhancement has been identified at the red wing of the H$\alpha$ line profile after the impulsive increase of the H$\alpha$ line intensity. The red wing enhancement corresponds to plasma moving away from the Earth at a velocity of 100$-$200 km s$^{-1}$. According to the current knowledge of solar flares, this red wing enhancement may originate from: (1) flare-driven coronal rain, (2) chromospheric condensation, or (3) a filament/prominence eruption that either with a non-radial backward propagation or with strong magnetic suppression. The total mass of the moving plasma is estimated to be on the order of $10^{15}$ kg.

Despite remarkable progress in image translation, the complex scene with multiple discrepant objects remains a challenging problem. The translated images have low fidelity and tiny objects in fewer details causing unsatisfactory performance in object recognition. Without thorough object perception (i.e., bounding boxes, categories, and masks) of images as prior knowledge, the style transformation of each object will be difficult to track in translation. We propose panoptic-aware generative adversarial networks (PanopticGAN) for image-to-image translation together with a compact panoptic segmentation dataset. The panoptic perception (i.e., foreground instances and background semantics of the image scene) is extracted to achieve alignment between object content codes of the input domain and panoptic-level style codes sampled from the target style space, then refined by a proposed feature masking module for sharping object boundaries. The image-level combination between content and sampled style codes is also merged for higher fidelity image generation. Our proposed method was systematically compared with different competing methods and obtained significant improvement in both image quality and object recognition performance., Comment: In 2023 IEEE winter conference on applications of computer vision (WACV)