arXiv subjects

Liyang Chen

Publications and source records attributed to Liyang Chen.

At least 37 records · Page 2Linked to original sources

arXiv2025

StableDub: Taming Diffusion Prior for Generalized and Efficient Visual Dubbing

The visual dubbing task aims to generate mouth movements synchronized with the driving audio, which has seen significant progress in recent years. However, two critical deficiencies hinder their wide application: (1) Audio-only driving paradigms inadequately capture speaker-specific lip habits, which fail to generate lip movements similar to the target avatar; (2) Conventional blind-inpainting approaches frequently produce visual artifacts when handling obstructions (e.g., microphones, hands), limiting practical deployment. In this paper, we propose StableDub, a novel and concise framework integrating lip-habit-aware modeling with occlusion-robust synthesis. Specifically, building upon the Stable-Diffusion backbone, we develop a lip-habit-modulated mechanism that jointly models phonemic audio-visual synchronization and speaker-specific orofacial dynamics. To achieve plausible lip geometries and object appearances under occlusion, we introduce the occlusion-aware training strategy by explicitly exposing the occlusion objects to the inpainting process. By incorporating the proposed designs, the model eliminates the necessity for cost-intensive priors in previous methods, thereby exhibiting superior training efficiency on the computationally intensive diffusion-based backbone. To further optimize training efficiency from the perspective of model architecture, we introduce a hybrid Mamba-Transformer architecture, which demonstrates the enhanced applicability in low-resource research scenarios. Extensive experimental results demonstrate that StableDub achieves superior performance in lip habit resemblance and occlusion robustness. Our method also surpasses other methods in audio-lip sync, video quality, and resolution consistency. We expand the applicability of visual dubbing methods from comprehensive aspects, and demo videos can be found at https://stabledub.github.io.

cs.CV↗

arXiv2025

HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning

Human-Centric Video Generation (HCVG) methods seek to synthesize human videos from multimodal inputs, including text, image, and audio. Existing methods struggle to effectively coordinate these heterogeneous modalities due to two challenges: the scarcity of training data with paired triplet conditions and the difficulty of collaborating the sub-tasks of subject preservation and audio-visual sync with multimodal inputs. In this work, we present HuMo, a unified HCVG framework for collaborative multimodal control. For the first challenge, we construct a high-quality dataset with diverse and paired text, reference images, and audio. For the second challenge, we propose a two-stage progressive multimodal training paradigm with task-specific strategies. For the subject preservation task, to maintain the prompt following and visual generation abilities of the foundation model, we adopt the minimal-invasive image injection strategy. For the audio-visual sync task, besides the commonly adopted audio cross-attention layer, we propose a focus-by-predicting strategy that implicitly guides the model to associate audio with facial regions. For joint learning of controllabilities across multimodal inputs, building on previously acquired capabilities, we progressively incorporate the audio-visual sync task. During inference, for flexible and fine-grained multimodal control, we design a time-adaptive Classifier-Free Guidance strategy that dynamically adjusts guidance weights across denoising steps. Extensive experimental results demonstrate that HuMo surpasses specialized state-of-the-art methods in sub-tasks, establishing a unified framework for collaborative multimodal-conditioned HCVG. Project Page: https://phantom-video.github.io/HuMo.

cs.CV↗

arXiv2025

BRIGHT+: Upgrading the BRIGHT Benchmark with MARCUS, a Multi-Agent RAG Clean-Up Suite

Retrieval-Augmented Generation (RAG) systems require corpora that are both structurally clean and semantically coherent. BRIGHT is a recent and influential benchmark designed to evaluate complex multi-hop retrieval across diverse, high-reasoning domains. However, its practical effectiveness is limited by common web-crawled artifacts - such as content redundancy and semantic discontinuity - that impair retrieval accuracy and downstream reasoning. Notably, we find that such issues are concentrated in seven StackExchange-derived subdomains, while other domains (e.g., Coding and Theorem-based content) remain relatively clean. In this study, we present MARCUS, a multi-agent pipeline that leverages large language models (LLMs) to systematically clean and re-chunk BRIGHT into a higher-quality corpus: BRIGHT-Plus. MARCUS applies dedicated agents for structural noise removal and semantic segmentation, preserving answer-bearing spans while improving contextual integrity. Experimental evaluations demonstrate that BRIGHT-Plus yields consistent and significant improvements in both retrieval accuracy and multi-hop reasoning across a diverse set of retrievers. We release both the BRIGHT-Plus corpus and the MARCUS pipeline to support future research on robust, reasoning-centric retrieval.

cs.AI↗

arXiv2025

Investigating the Period-Luminosity Relations of delta Scuti Stars: A Pathway to Distance and 3-D Dust Map Inference

While delta Scuti stars are the most numerous class of kappa-mechanism pulsators in the instability strip, the short periods and small peak-to-peak amplitudes have left them understudied and underutilized. Recently, large-scale time-domain surveys have significantly increased the number of identified delta Scuti stars. Notably, the Tsinghua University-Ma Huateng Telescopes for Survey (TMTS), with its high-cadence observations at 1-minute intervals, has identified thousands of delta Scuti stars, greatly expanding the sample of these short-period pulsating variables. Using the delta Scuti stars from the TMTS catalogs of Periodic Variable Stars, we cross-matched the dataset with Pan-STARRS1, 2MASS, and WISE to obtain photometric measurements across optical and infrared bands. Parallax data, used as Bayesian priors, were retrieved from Gaia DR3, and line-of-sight dust extinction priors were estimated from a three-dimensional dust map. Using PyMC, we performed a simultaneous determination of the 11-band P-L relations of delta Scuti stars, which not only yields precise measurements of these relations, but also greatly improves constraints on the distance moduli and color excesses, as evidenced by the reduced uncertainties in the posterior distributions. Furthermore, our methodology enables an independent estimation of the color excess through the P-L relations, offering a potential complement to existing 3-D dust maps. Moreover, by cross-matching with LAMOST DR7, we investigated the influence of metallicity on the P-L relations. Our analysis reveals that incorporating metallicity might reduce the intrinsic scatter at longer wavelengths. However, this result does not achieve 3 sigma significance, leaving open the possibility that the observed reduction is attributable to statistical fluctuations.

astro-ph.SR↗

arXiv2025

Optical and Near-infrared Observations of SN 2023ixf for over 600 days after the Explosion

Context.We present a comprehensive photometric and spectroscopic study of the nearby Type II supernova (SN) 2023ixf, with our extensive observations spanning the phases from ~3 to over 600 days after the first light.\\ Aims.The aim of this study is to obtain key information on the explosion properties of SN\,2023ixf and the nature of its progenitor.\\ Methods.The observational properties of SN\,2023ixf are compared with those of a sample of Type IIP/L SNe to investigate commonalities and diversities. We conduct a detailed analysis of temporal evolution of major spectral features observed throughout different phases of the SN\,2023ixf explosion. Several interpretations are addressed through a comparison between the data and the model spectra for progenitor stars within a range of zero-age main sequence (ZAMS) masses.\\ Results.Our observations indicate that SN\,2023ixf is a transitional SN that bridges the gap between Type IIP and IIL subclasses of H-rich SNe, characterized by a relatively short plateau ($\lesssim 70$\,d) in the light curve. It shows a rather prompt spectroscopic evolution toward the nebular phase; emission lines of Na, O, H, and Ca in nebular spectra all exhibit multipeak profiles, which might be attributed to bipolar distribution of the ejecta. In particular, the H$α$ profile can be separated into two central peaked components (with a velocity of about 1500\,km\,s$^{-1}$) that is likely due to nickel-powered ejecta and two outer peak/box components (with a velocity extending up to ~8000 km\,s$^{-1}$) that can arise from interaction of the outermost ejecta with a circumstellar shell at a distance of $\sim6.2\times10^{15}$cm. The nebular-phase spectra of SN\,2023ixf show good agreement with those predicted by model spectra for progenitor stars with a ZAMS mass ranging from 15 to 19\,M${_\odot}$. A distance $D = 6.35^{+0.31}_{-0.39}$\,Mpc is estimated for M101.

astro-ph.HE↗

arXiv2025

AdaMesh: Personalized Facial Expressions and Head Poses for Adaptive Speech-Driven 3D Facial Animation

Speech-driven 3D facial animation aims at generating facial movements that are synchronized with the driving speech, which has been widely explored recently. Existing works mostly neglect the person-specific talking style in generation, including facial expression and head pose styles. Several works intend to capture the personalities by fine-tuning modules. However, limited training data leads to the lack of vividness. In this work, we propose AdaMesh, a novel adaptive speech-driven facial animation approach, which learns the personalized talking style from a reference video of about 10 seconds and generates vivid facial expressions and head poses. Specifically, we propose mixture-of-low-rank adaptation (MoLoRA) to fine-tune the expression adapter, which efficiently captures the facial expression style. For the personalized pose style, we propose a pose adapter by building a discrete pose prior and retrieving the appropriate style embedding with a semantic-aware pose style matrix without fine-tuning. Extensive experimental results show that our approach outperforms state-of-the-art methods, preserves the talking style in the reference video, and generates vivid facial animation. The supplementary video and code will be available at https://adamesh.github.io.

cs.CV↗

arXiv2025

Asymmetries and Circumstellar Interaction in the Type II SN 2024bch

We present a comprehensive multi-epoch photometric and spectroscopic study of SN 2024bch, a nearby (19.9 Mpc) Type II supernova (SN) with prominent early high ionization emission lines. Optical spectra from 2.9 days after the estimated explosion reveal narrow lines of H I, He II, C IV, and N IV that disappear by day 6. High cadence photometry from the ground and TESS show that the SN brightened quickly and reached a peak M$_V \sim$ $-$17.8 mag within a week of explosion, and late-time photometry suggests a $^{56}$Ni mass of 0.050 M$_{\odot}$. High-resolution spectra from day 8 and 43 trace the unshocked circumstellar medium (CSM) and indicate a wind velocity of 30--40 km s$^{-1}$, a value consistent with a red supergiant (RSG) progenitor. Comparisons between models and the early spectra suggest a pre-SN mass-loss rate of $\dot{M} \sim 10^{-3}-10^{-2}\ M_\odot\ \mathrm{yr}^{-1}$, which is too high to be explained by quiescent mass loss from RSGs, but is consistent with some recent measurements of similar SNe. Persistent blueshifted H I and [O I] emission lines seen in the optical and NIR spectra could be produced by asymmetries in the SN ejecta, while the multi-component H$α$ may indicate continued interaction with an asymmetric CSM well into the nebular phase. SN 2024bch provides another clue to the complex environments and mass-loss histories around massive stars.

astro-ph.HE↗

arXiv2024

Shot noise and universal Fano factor as characterization of strongly correlated metals

Shot noise measures out-of-equilibrium current fluctuations and is a powerful tool to probe the nature of current-carrying excitations in quantum systems. Recent shot noise measurements in the heavy fermion strange metal YbRh$_2$Si$_2$ exhibit a strong suppression of the Fano factor ($F$) -- the ratio of the current noise to the average current in the DC limit. This system is representative of metals in which electron correlations are extremely strong. Here we carry out the first theoretical study on the shot noise of diffusive metals in the regime of strong correlations. A Boltzmann-Langevin equation formulation is constructed in a quasiparticle description in the presence of strong correlations. We find that $F = \sqrt{ 3}/{4}$ in such a correlation regime. Thus, we establish the aforementioned Fano factor as universal to Fermi liquids, and show that the Fano factor suppression observed in experiments on YbRh$_2$Si$_2$ necessitates a loss of the quasiparticles. Our work opens the door to systematic theoretical studies of shot noise as a means of characterizing strongly correlated metallic phases and materials.

cond-mat.str-el↗

arXiv2024

VAST: Vivify Your Talking Avatar via Zero-Shot Expressive Facial Style Transfer

Current talking face generation methods mainly focus on speech-lip synchronization. However, insufficient investigation on the facial talking style leads to a lifeless and monotonous avatar. Most previous works fail to imitate expressive styles from arbitrary video prompts and ensure the authenticity of the generated video. This paper proposes an unsupervised variational style transfer model (VAST) to vivify the neutral photo-realistic avatars. Our model consists of three key components: a style encoder that extracts facial style representations from the given video prompts; a hybrid facial expression decoder to model accurate speech-related movements; a variational style enhancer that enhances the style space to be highly expressive and meaningful. With our essential designs on facial style learning, our model is able to flexibly capture the expressive facial style from arbitrary video prompts and transfer it onto a personalized image renderer in a zero-shot manner. Experimental results demonstrate the proposed approach contributes to a more vivid talking avatar with higher authenticity and richer expressiveness.

cs.CV↗

arXiv2024

MagicMan: Generative Novel View Synthesis of Humans with 3D-Aware Diffusion and Iterative Refinement

Existing works in single-image human reconstruction suffer from weak generalizability due to insufficient training data or 3D inconsistencies for a lack of comprehensive multi-view knowledge. In this paper, we introduce MagicMan, a human-specific multi-view diffusion model designed to generate high-quality novel view images from a single reference image. As its core, we leverage a pre-trained 2D diffusion model as the generative prior for generalizability, with the parametric SMPL-X model as the 3D body prior to promote 3D awareness. To tackle the critical challenge of maintaining consistency while achieving dense multi-view generation for improved 3D human reconstruction, we first introduce hybrid multi-view attention to facilitate both efficient and thorough information interchange across different views. Additionally, we present a geometry-aware dual branch to perform concurrent generation in both RGB and normal domains, further enhancing consistency via geometry cues. Last but not least, to address ill-shaped issues arising from inaccurate SMPL-X estimation that conflicts with the reference image, we propose a novel iterative refinement strategy, which progressively optimizes SMPL-X accuracy while enhancing the quality and consistency of the generated multi-views. Extensive experimental results demonstrate that our method significantly outperforms existing approaches in both novel view synthesis and subsequent 3D human reconstruction tasks.

cs.CV↗

arXiv2024

Minute-Cadence Observations of the LAMOST Fields with the TMTS: IV -- Catalog of Cataclysmic Variables from the First 3-yr Survey

The Tsinghua University--Ma Huateng Telescopes for Survey (TMTS) started to monitor the LAMOST plates in 2020, leading to the discovery of numerous short-period eclipsing binaries, peculiar pulsators, flare stars, and other variable objects. Here, we present the uninterrupted light curves for a sample of 64 cataclysmic variables (CVs) observed/discovered using the TMTS during its first three-year observations, and we introduce new CVs and new light-variation periods (from known CVs) revealed through the TMTS observations. Thanks to the high-cadence observations of TMTS, diverse light variations, including superhumps, quasi-periodic oscillations, large-amplitude orbital modulations, and rotational modulations, are able to be detected in our CV samples, providing key observational clues for understanding the fast-developing physical processes in various CVs. All of these short-timescale light-curve features help further classify the subtypes of CV systems. We highlight the light-curve features observed in our CV sample and discuss further implications of minute-cadence light curves for CV identifications and classifications. Moreover, we examine the H$α$ emission lines in the spectra from our nonmagnetic CV samples (i.e., dwarf novae and nova-like subclasses) and find that the distribution of H$α$ emission strength shows significant differences between the sources with orbital periods above and below the period gap, which agrees with the trend seen from the SDSS nonmagnetic CV sample.

astro-ph.SR↗

arXiv2024

Low temperature spin Seebeck effect in non-magnetic vanadium dioxide

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination.

cond-mat.str-el↗

arXiv2024

The Red Supergiant Progenitor of Type II Supernova 2024ggi

We present a detailed analysis of the progenitor and its local environment for the recently discovered type II supernova (SN) 2024ggi at a distance of about 6.7~Mpc, by utilizing the pre-explosion images from the Hubble Space Telescope (HST) and \textit{Spitzer} Space Telescope. The progenitor is identified as a red, bright variable star, with absolute $F814W$-band magnitudes being $-$6.2 mag in 1995 to $-$7.2 mag in 2003, respectively, consistent with that of a normal red supergiant (RSG) star. Combining with the historical mid-infrared light curves, a pulsational period of about 379~days can be inferred for the progenitor star. Fitting its spectral energy distribution with stellar spectral models yields the stellar parameters of temperature, radius and bolometric luminosity as $T_*=3290_{-27}^{+19}$~K, $R_*=887_{-51}^{+60}$~R$_{\odot}$, and log($L$/L$_{\odot}$)$=4.92_{-0.04}^{+0.05}$, respectively. The above parameters indicate that the progenitor of SN 2024ggi is consistent with the stellar evolutionary track of a solar-metallicity massive star with an initial mass of $13_{-1}^{+1}$~M$_{\odot}$. Moreover, our analysis indicates a relatively low mass loss rate (i.e., $< 3\times10^{-6}$~M$_{\odot}$~yr$^{-1}$) for the progenitor compared to that inferred from the flashed spectra and X-ray detection (i.e., $10^{-2}$$-$$ 10$$^{-5}$~M$_{\odot}$~yr$^{-1}$), implying a significant enhancement in mass loss within a few years prior to the explosion.

astro-ph.HE↗

arXiv2024

Improving Language Model-Based Zero-Shot Text-to-Speech Synthesis with Multi-Scale Acoustic Prompts

Zero-shot text-to-speech (TTS) synthesis aims to clone any unseen speaker's voice without adaptation parameters. By quantizing speech waveform into discrete acoustic tokens and modeling these tokens with the language model, recent language model-based TTS models show zero-shot speaker adaptation capabilities with only a 3-second acoustic prompt of an unseen speaker. However, they are limited by the length of the acoustic prompt, which makes it difficult to clone personal speaking style. In this paper, we propose a novel zero-shot TTS model with the multi-scale acoustic prompts based on a neural codec language model VALL-E. A speaker-aware text encoder is proposed to learn the personal speaking style at the phoneme-level from the style prompt consisting of multiple sentences. Following that, a VALL-E based acoustic decoder is utilized to model the timbre from the timbre prompt at the frame-level and generate speech. The experimental results show that our proposed method outperforms baselines in terms of naturalness and speaker similarity, and can achieve better performance by scaling out to a longer style prompt.

cs.SD↗

arXiv2024

The challenges of measuring spin Seebeck noise

Just as electronic shot noise in driven conductors results from the granularity of charge and the statistical variation in the arrival times of charge carriers, there are predictions for fundamental noise in magnon currents due to angular momentum being carried by discrete excitations. The inverse spin Hall effect as a transduction mechanism to convert spin current into charge current raises the prospect of experimental investigations of such magnon shot noise. Spin Seebeck effect measurements have demonstrated the electrical detection of thermally driven magnon currents and have been suggested as an avenue for accessing spin current fluctuations. Using spin Seebeck structures made from yttrium iron garnet on gadolinium gallium garnet, we demonstrate the technical challenges inherent in such noise measurements. While there is a small increase in voltage noise in the inverse spin Hall detector at low temperatures associated with adding a magnetic field, the dependence on field orientation implies that this is not due to magnon shot noise. We describe theoretical predictions for the expected magnitude of magnon shot noise, highlighting ambiguities that exist. Further, we show that magnon shot noise detection through the standard inverse spin Hall approach is likely impossible due to geometric factors. Implications for future attempts to measure magnon shot noise are discussed.

cond-mat.mes-hall↗

arXiv2024

Enhancing Expressiveness in Dance Generation via Integrating Frequency and Music Style Information

Dance generation, as a branch of human motion generation, has attracted increasing attention. Recently, a few works attempt to enhance dance expressiveness, which includes genre matching, beat alignment, and dance dynamics, from certain aspects. However, the enhancement is quite limited as they lack comprehensive consideration of the aforementioned three factors. In this paper, we propose ExpressiveBailando, a novel dance generation method designed to generate expressive dances, concurrently taking all three factors into account. Specifically, we mitigate the issue of speed homogenization by incorporating frequency information into VQ-VAE, thus improving dance dynamics. Additionally, we integrate music style information by extracting genre- and beat-related features with a pre-trained music model, hence achieving improvements in the other two factors. Extensive experimental results demonstrate that our proposed method can generate dances with high expressiveness and outperforms existing methods both qualitatively and quantitatively.

cs.MM↗

arXiv2024

A seven-Earth-radius helium-burning star inside a 20.5-min detached binary

Binary evolution theory predicts that the second common envelope (CE) ejection can produce low-mass (0.32-0.36 Msun) subdwarf B (sdB) stars inside ultrashort-orbital-period binary systems, as their helium cores are ignited under nondegenerate conditions. With the orbital decay driven by gravitational-wave (GW) radiation, the minimum orbital periods of detached sdB binaries could be as short as ~20 minutes. However, only four sdB binaries with orbital periods below an hour have been reported so far, while none of them has an orbital period approaching the above theoretical limit. Here we report the discovery of a 20.5-minute-orbital-period ellipsoidal binary, TMTS J052610.43+593445.1, in which the visible star is being tidally deformed by an invisible carbon-oxygen white dwarf (WD) companion. The visible component is inferred to be an sdB star with a mass of ~0.33 Msun, approaching that of helium-ignition limit, although a He-core WD cannot be completely ruled out. In particular, the radius of this low-mass sdB star is only 0.066 Rsun, about seven Earth radii, possibly representing the most compact nondegenerate star ever known. Such a system provides a key clue to map the binary evolution scheme from the second CE ejection to the formation of AM CVn stars having a helium-star donor, and it will also serve as a crucial verification binary of space-borne GW detectors in the future.

astro-ph.SR↗

arXiv2024

Minute-Cadence Observations of the LAMOST Fields with the TMTS V. Machine Learning Classification of TMTS Catalogues of Periodic Variable Stars

Periodic variables are always of great scientific interest in astrophysics. Thanks to the rapid advancement of modern large-scale time-domain surveys, the number of reported variable stars has experienced substantial growth for several decades, which significantly deepened our comprehension of stellar structure and binary evolution. The Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) has started to monitor the LAMOST sky areas since 2020, with a cadence of 1 minute. During the period from 2020 to 2022, this survey has resulted in densely sampled light curves for ~ 30,000 variables of the maximum powers in the Lomb-Scargle periodogram above the 5sigma threshold. In this paper, we classified 11,638 variable stars into 6 main types using XGBoost and Random Forest classifiers with accuracies of 98.83% and 98.73%, respectively. Among them, 5301 (45.55%) variables are newly discovered, primarily consisting of Delta Scuti stars, demonstrating the capability of TMTS in searching for short-period variables. We cross-matched the catalogue with Gaia's second Data Release (DR2) and LAMOST's seventh Data Release (DR7) to obtain important physical parameters of the variables. We identified 5504 Delta Scuti stars (including 4876 typical Delta Scuti stars and 628 high-amplitude Delta Scuti stars), 5899 eclipsing binaries (including EA-, EB- and EW-type) and 226 candidates of RS Canum Venaticorum. Leveraging the metal abundance data provided by LAMOST and the Galactic latitude, we discovered 8 candidates of SX Phe stars within the class of "Delta Scuti stars". Moreover, with the help of Gaia color-magnitude diagram, we identified 9 ZZ ceti stars.

astro-ph.SR↗