arXiv subjects

Yichen Sun

Publications and source records attributed to Yichen Sun.

15 recordsLinked to original sources

arXiv2026

Low-energy Muon-Nucleon scattering experiment: LUNE (White Paper)

The HIAF will provide high-intensity, high-quality muon beams with momenta from 0.5 to 7.5 GeV/c. This energy range is uniquely suited for precision muon scattering, bridging the gap between low-energy electron facilities and future high-energy lepton-ion colliders. In particular, HIAF will enable precision measurements with both positive and negative muon beams over a broad kinematic range, complementing existing electron-scattering facilities such as JLab, EicC and EIC. Based on HIAF muon source, the LUNE Collaboration has been established to address several fundamental questions in nuclear and particle physics, including the proton charge radius puzzle, nucleon electromagnetic structure, and the dynamics of quantum electrodynamics and hadronic interactions. The program proceeds in two phases, from elastic scattering to nucleon structure and beyond-Standard-Model searches. The experiment is expected to determine the proton charge radius with a precision of approximately 1.0\% using elastic muon-proton scattering. It will also perform systematic measurements of the proton electromagnetic form factors with both $\mu^+$ and $\mu^-$ beams, enabling precise studies of two-photon exchange effects and stringent tests of quantum electrodynamics. Beyond elastic scattering, LUNE will investigate TMD, gravitational form factors, and nuclear charge radii, providing new insights into the 3D structure of nucleons and nuclei. The experiment will further address important topics including Coulomb-distortion corrections, nuclear medium effects, and possible signatures of physics beyond the Standard Model. This white paper presents the scientific motivation, detector concept, expected performance, and long-term strategy of LUNE.

hep-ex↗

arXiv2026

Uncertainty-Aware Reward Modeling for Stable RLHF

Reinforcement learning from human feedback (RLHF) aligns large language models by training reward models on preference data and optimizing policies to maximize predicted rewards. However, this pipeline faces two fundamental challenges: (1) reward models cannot signal when their predictions are unreliable, since they usually act as deterministic point estimators; and (2) modern group-based policy optimization can amplify unreliable reward signals, as exemplified by GRPO's uniform treatment of rewards during advantage computation. As policies explore increasingly diverse responses, these two limitations create a critical vulnerability: unreliable reward estimates may be granted disproportionate influence, triggering severe reward hacking. We propose Uncertainty-Aware Reward Modeling (UARM), which equips reward models with calibrated uncertainty via quantile-based conformal prediction and reweights GRPO advantages through heteroscedastic variance decomposition. Experiments across HelpSteer, UltraFeedback, and PKU-SafeRLHF demonstrate that UARM significantly improves reward model calibration, reduces reward hacking, and enhances downstream alignment quality compared to standard GRPO and uncertainty-agnostic baselines.

cs.LG↗

arXiv2026

Fixturize: Bridging the Fixture Gap in Test Generation

Current Large Language Models (LLMs) have advanced automated unit test generation but face a critical limitation: they often neglect to construct the necessary test fixtures, which are the environmental setups required for a test to run. To bridge this gap, this paper proposes Fixturize, a diagnostic framework that proactively identifies fixture-dependent functions and synthesizes test fixtures accordingly through an iterative, feedback-driven process, thereby improving the quality of auto-generated test suites of existing approaches. For rigorous evaluation, the authors introduce FixtureEval, a dedicated benchmark comprising 600 curated functions across two Programming Languages (PLs), i.e., Python and Java, with explicit fixture dependency labels, enabling both the corresponding classification and generation tasks. Empirical results demonstrate that Fixturize is highly effective, achieving 88.38%-97.00% accuracy across benchmarks in identifying the dependence of test fixtures and significantly enhancing the Suite Pass rate (SuitePS) by 18.03%-42.86% on average across both PLs with the auto-generated fixtures. Owing to the maintenance of test fixtures, Fixturize further improves line/branch coverage when integrated with existing testing tools of both LLM-based and Search-based by 16.85%/24.08% and 31.54%/119.66% on average, respectively. The findings establish fixture awareness as an essential, missing component in modern auto-testing pipelines.

cs.SE↗

arXiv2025

SWAP: Towards Copyright Auditing of Soft Prompts via Sequential Watermarking

Large-scale vision-language models, especially CLIP, have demonstrated remarkable performance across diverse downstream tasks. Soft prompts, as carefully crafted modules that efficiently adapt vision-language models to specific tasks, necessitate effective copyright protection. In this paper, we investigate model copyright protection by auditing whether suspicious third-party models incorporate protected soft prompts. While this can be viewed as a special case of model ownership auditing, our analysis shows that existing techniques are ineffective due to prompt learning's unique characteristics. Non-intrusive auditing is inherently prone to false positives when independent models share similar data distributions with victim models. Intrusive approaches also fail: backdoor methods designed for CLIP cannot embed functional triggers, while extending traditional DNN backdoor techniques to prompt learning suffers from harmfulness and ambiguity challenges. We find that these failures in intrusive auditing stem from the same fundamental reason: watermarking operates within the same decision space as the primary task yet pursues opposing objectives. Motivated by these findings, we propose sequential watermarking for soft prompts (SWAP), which implants watermarks into a different and more complex space. SWAP encodes watermarks through a specific order of defender-specified out-of-distribution classes, inspired by the zero-shot prediction capability of CLIP. This watermark, which is embedded in a more complex space, keeps the original prediction label unchanged, making it less opposed to the primary task. We further design a hypothesis-test-guided verification protocol for SWAP and provide a theoretical analysis of when verification works. Extensive experiments on 11 datasets demonstrate SWAP's effectiveness, harmlessness, and robustness against potential attacks.

cs.CR↗

arXiv2025

Scientific Objectives of the Xue-shan-mu-chang 15-meter Submillimeter Telescope

Submillimeter astronomy is poised to revolutionize our understanding of the Universe by revealing cosmic phenomena hidden from optical and near-infrared observations, particularly those associated with interstellar dust, molecular gas, and star formation. The Xue-shan-mu-chang 15-meter submillimeter telescope (XSMT-15m), to be constructed at a premier high-altitude site (4813 m) in Qinghai, China, marks a major milestone for Chinese astronomy, establishing the China mainland's first independently developed, world-class submillimeter facility. Equipped with state-of-the-art instruments, XSMT-15m will address a diverse range of frontier scientific questions spanning extragalactic astronomy, Galactic structure, time-domain astrophysics, and astrochemistry. In synergy with current and forthcoming observatories, XSMT-15m will illuminate the formation and evolution of galaxies, unravel the physical and chemical processes shaping the interstellar medium, and explore transient phenomena in the submillimeter regime. These capabilities will advance our understanding across extragalactic astronomy, Galactic ecology, astrochemistry, and time-domain astrophysics, inaugurating a new era for submillimeter research in China and the northern hemisphere.

astro-ph.GA↗

arXiv2025

Dynamic Incentive Strategies for Smart EV Charging Stations: An LLM-Driven User Digital Twin Approach

This paper presents an enhanced electric vehicle demand response system based on large language models, aimed at optimizing the application of vehicle-to-grid technology. By leveraging an large language models-driven multi-agent framework to construct user digital twins integrated with multidimensional user profile features, it enables deep simulation and precise prediction of users' charging and discharging decision-making patterns. Additionally, a data- and knowledge-driven dynamic incentive mechanism is proposed, combining a distributed optimization model under network constraints to optimize the grid-user interaction while ensuring both economic viability and security. Simulation results demonstrate that the approach significantly improves load peak-valley regulation and charging/discharging strategies. Experimental validation highlights the system's substantial advantages in load balancing, user satisfaction and grid stability, providing decision-makers with a scalable V2G management tool that promotes the sustainable, synergistic development of vehicle-grid integration.

eess.SY↗

arXiv2025

Inadequate turbulent support in low-metallicity molecular clouds

The dynamic properties of molecular clouds are set by the interplay of their self-gravity, turbulence, external pressure and magnetic fields. Extended surveys of Galactic molecular clouds typically find that their kinetic energy ($E_{\rm k}$) counterbalances their self-gravitational energy ($E_{\rm g}$), setting their virial parameter $\alpha_{\rm vir}=2E_{\rm k}/|E_{\rm g}|\approx1$. However, past studies either have been biased by the use of optically-thick lines or have been limited within the solar neighborhood and the inner Galaxy (Galactocentric radius $R_{\rm gc}<R_{\rm gc,\odot} \approx 8$ kpc). Here we present sensitive mapping observations of optically thin $^{13}$CO lines towards molecular clouds in the low-metallicity Galactic outer disk ($R_{\rm gc}\sim9-24$ kpc). By combining archival data from the inner Galaxy and four nearby metal-poor dwarf galaxies, we reveal a systematic trend of $\alpha_{\rm vir}$, which declines from supervirial dynamic states in metal-rich clouds to extremely subvirial dynamic states in metal-poor clouds. In these metal-poor environments, turbulence alone is insufficient to counterbalance the self-gravity of a cloud. A cloud-volumetric magnetic field may replace turbulence as the dominant cloud-supporting mechanism in low-metallicity conditions, for example, the outermost galactic disks, dwarf galaxies and galaxies in the early Universe, which would then inevitably impact the initial conditions for star formation in such environments.

astro-ph.GA↗

arXiv2024

A new measurement of the Galactic $^{12}$C/$^{13}$C gradient from sensitive HCO$^+$ absorption observations

We present a new constraint on the Galactic $^{12}$C/$^{13}$C gradient with sensitive HCO$^+$ absorption observations against strong continuum sources. The new measurements suffer less from beam dilution, optical depths, and chemical fractionation, allowing us to derive the isotopic ratios precisely. The measured $^{12}$C/$^{13}$C ratio in the Solar neighborhood (66$\pm$5) is consistent with those obtained from CH$^+$. Two measurements toward the Galactic Center are 42.2$\pm$1.7 and 37.5$\pm$6.5. Though the values are a factor of 2$\sim$3 higher than those derived from dense gas tracers (e.g., H$_2$CO, complex organic molecules) toward Sagittarius (Sgr) B2 regions, our results are consistent with the absorption measurements from c-C$_3$H$_2$ toward Sgr B2 ($\sim$40), and those from CH$^+$ toward Sgr A$^*$ and Sgr B2(N) ($>$30). We calculate a new Galactic $^{12}$C/$^{13}$C gradient of (6.4$\pm$1.9)$R_{\rm GC}$/kpc+(25.9$\pm$10.5), and find an increasing trend of $^{12}$C/$^{13}$C gradient obtained from high-density to low-density gas tracers, suggesting opacity effects and chemical fractionation may have a strong impact on the isotopic ratios observed at high-density regions.

astro-ph.GA↗

arXiv2024

Prompt-Consistency Image Generation (PCIG): A Unified Framework Integrating LLMs, Knowledge Graphs, and Controllable Diffusion Models

The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that contradict the input text, which poses a challenge to their reliability and practical deployment. To address this problem, we introduce a novel diffusion-based framework to significantly enhance the alignment of generated images with their corresponding descriptions, addressing the inconsistency between visual output and textual input. Our framework is built upon a comprehensive analysis of inconsistency phenomena, categorizing them based on their manifestation in the image. Leveraging a state-of-the-art large language module, we first extract objects and construct a knowledge graph to predict the locations of these objects in potentially generated images. We then integrate a state-of-the-art controllable image generation model with a visual text generation module to generate an image that is consistent with the original prompt, guided by the predicted object locations. Through extensive experiments on an advanced multimodal hallucination benchmark, we demonstrate the efficacy of our approach in accurately generating the images without the inconsistency with the original prompt. The code can be accessed via https://github.com/TruthAI-Lab/PCIG.

cs.CV↗

arXiv2024

Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models

The rapid advancement in text-to-video (T2V) generative models has enabled the synthesis of high-fidelity video content guided by textual descriptions. Despite this significant progress, these models are often susceptible to hallucination, generating contents that contradict the input text, which poses a challenge to their reliability and practical deployment. To address this critical issue, we introduce the SoraDetector, a novel unified framework designed to detect hallucinations across diverse large T2V models, including the cutting-edge Sora model. Our framework is built upon a comprehensive analysis of hallucination phenomena, categorizing them based on their manifestation in the video content. Leveraging the state-of-the-art keyframe extraction techniques and multimodal large language models, SoraDetector first evaluates the consistency between extracted video content summary and textual prompts, then constructs static and dynamic knowledge graphs (KGs) from frames to detect hallucination both in single frames and across frames. Sora Detector provides a robust and quantifiable measure of consistency, static and dynamic hallucination. In addition, we have developed the Sora Detector Agent to automate the hallucination detection process and generate a complete video quality report for each input video. Lastly, we present a novel meta-evaluation benchmark, T2VHaluBench, meticulously crafted to facilitate the evaluation of advancements in T2V hallucination detection. Through extensive experiments on videos generated by Sora and other large T2V models, we demonstrate the efficacy of our approach in accurately detecting hallucinations. The code and dataset can be accessed via GitHub.

cs.LG↗

arXiv2024

The CO-dark molecular gas in the cold HI arc

The CO-dark molecular gas (DMG), which refers to the molecular gas not traced by CO emission, is crucial for the evolution of the interstellar medium (ISM). While the gas properties of DMG have been widely explored in the Solar neighborhood, whether or not they are similar in the outer disk regions of the Milky Way is still not well understood. In this Letter, we confirm the existence of DMG toward a cold HI arc structure at 13 kpc away from the Galactic center with both OH emission and HI narrow self-absorption (HINSA). This is the first detection of HINSA in the outer disk region, in which the HINSA fraction ($N_{\rm HINSA}$/$N_{\rm H_2}$ = 0.022$\pm$0.011) is an order of magnitude higher than the average value observed in nearby evolved dark clouds, but is consistent with that of the early evolutionary stage of dark clouds. The inferred H$_2$ column density from both extinction and OH emission ($N_{\rm H_2} \approx 10^{20}$ cm$^{-2}$) is an order of magnitude higher than previously estimated. Although the ISM environmental parameters are expected to be different between the outer Galactic disk regions and the Solar neighborhood, we find that the visual extinction ($A_{\rm V}$ = 0.19$\pm$0.03 mag), H$_2$-gas density ($n_{\rm H_2} = 91\pm46$ cm$^{-3}$), and molecular fraction (58\%$\pm$28\%) of the DMG are rather similar to those of nearby diffuse molecular clouds. The existence of DMG associated with the expanding HI supershell supports a scenario where the expansion of supershells may trigger the formation of molecular clouds within a crossing timescale of the shock wave ($\sim$10$^6$ yr).

astro-ph.GA↗

arXiv2023

$\alpha$-enhanced Astrochemistry: the Carbon cycle in extreme galactic conditions

Astrochemistry has been widely developed as a power tool to probe physical properties of the interstellar medium (ISM) in various conditions of the Milky Way (MW) Galaxy, and in near and distant galaxies. Most current studies conventionally apply linear scaling to all elemental abundances based on the gas-phase metallicity. However, these elements, including carbon and oxygen, are enriched differentially by stellar nucleosynthesis and the overall galactic chemical evolution, evident from $\alpha$-enhancement in multiple galactic observations such as starbursts, high-redshift star-forming galaxies, and low-metallicity dwarfs. We perform astrochemical modeling to simulate the impact of an $\alpha$-enhanced ISM gas cloud on the abundances of the three phases of carbon (C$^+$, C, CO) dubbed as `the carbon cycle'. The ISM environmental parameters considered include two cosmic-ray ionization rates ($\zeta_{\rm CR}=10^{-17}$ and $10^{-15}\,{\rm s}^{-1}$), two isotropic FUV radiation field strengths ($\chi/\chi_0=1$ and $10^2$), and (sub-)linear dust-to-gas relations against metallicity, mimicking the ISM conditions of different galaxy types. In galaxies with [C/O] $<$ 0, CO, C and C$^+$ all decrease in both abundances and emission, though with differential biases. The low-$J$ CO emission is found to be the most stable tracer for the molecular gas, while C and C$^+$ trace H$_2$ gas only under limited conditions, in line with recent discoveries of [CI]-dark galaxies. We call for caution when using [CII]~$158\mu$m and [CI](1-0) as alternative H$_2$-gas tracers for both diffuse and dense gas with non-zero [C/O] ratios.

astro-ph.GA↗

arXiv2023

An improved method to measure $\rm ^{12}C/^{13}C$ and $\rm ^{14}N/^{15}N$ abundance ratios: revisiting CN isotopologues in the Galactic outer disk

The variations of elemental abundance and their ratios along the Galactocentric radius result from the chemical evolution of the Milky Way disks. The $\rm ^{12}C/^{13}C$ ratio in particular is often used as a proxy to determine other isotopic ratios, such as $\rm ^{16}O/^{18}O$ and $\rm ^{14}N/^{15}N$. Measurements of $\rm ^{12}CN$ and $\rm ^{13}CN$ (or $\rm C^{15}N$) -- with their optical depths corrected via their hyper-fine structure lines -- have traditionally been exploited to constrain the Galactocentric gradients of the CNO isotopic ratios. Such methods typically make several simplifying assumptions (e.g. a filling factor of unity, the Rayleigh-Jeans approximation, and the neglect of the cosmic microwave background) while adopting a single average gas phase. However, these simplifications introduce significant biases to the measured $\rm ^{12}C/^{13}C$ and $\rm ^{14}N/^{15}N$. We demonstrate that exploiting the optically thin satellite lines of $\rm ^{12}CN$ constitutes a more reliable new method to derive $\rm ^{12}C/^{13}C$ and $\rm ^{14}N/^{15}N$ from CN isotopologues. We apply this satellite-line method to new IRAM 30-m observations of $\rm ^{12}CN$, $\rm ^{13}CN$, and $\rm C^{15}N$ $N=1\to0$ towards 15 metal-poor molecular clouds in the Galactic outer disk ($R_{\rm gc} > $ 12 kpc), supplemented by data from the literature. After updating their Galactocentric distances, we find that $\rm ^{12}C/^{13}C$ and $\rm ^{14}N/^{15}N$ gradients are in good agreement with those derived using independent optically thin molecular tracers, even in regions with the lowest metallicities. We therefore recommend using optically thin tracers for Galactic and extragalactic CNO isotopic measurements, which avoids the biases associated with the traditional method.

astro-ph.GA↗

arXiv2022

Properties of dense molecular gas along the major axis of M 82

Dense gas is important for galaxy evolution and star formation. Optically-thin dense-gas tracers, such as isotopologues of HCN, HCO+, etc., are very helpful to diagnose excitation conditions of dense molecular gas. However, previous studies of optically-thin dense-gas tracers were mostly focusing on average properties of galaxies as a whole, due to limited sensitivity and angular resolution. M82, a nearby prototype starburst galaxy, offers a unique case for spatially-resolved studies with single-dish telescopes. With the IRAM 30-m telescope, we observed the J = 1 - 0 transition of H13CN, HC15N, H13CO+, HN13C, H15NC, and SiO J = 2 - 1, HC3N J= 10 - 9, H2CO J = 2 - 1 toward five positions along the major axis of M82. The intensity ratios of I(HCN)/I(H13CN) and I(HCO+)/I(H13CO+) show a significant spatial variation along the major axis, with lower values in the central region than those on the disk, indicating higher optical depths in the central region. The optical depths of HCO+ lines are found to be systematically higher than those of HCN lines at all positions. Futhermore, we find that the 14N/15N ratios have an increasing gradient from the center to the outer disk.

astro-ph.GA↗

arXiv2020

Pressure-tuned intralayer exchange in superlattice-like MnBi2Te4/(Bi2Te3)n topological insulators

The magnetic structures of MnBi2Te4(Bi2Te3)n can be manipulated by tuning the interlayer coupling via the number of Bi2Te3 spacer layers n, while the intralayer ferromagnetic (FM) exchange coupling is considered too robust to control. By applying hydrostatic pressure up to 3.5 GPa, we discover opposite responses of magnetic properties for n = 1 and 2. MnBi4Te7 stays at A-type antiferromagnetic (AFM) phase with a decreasing N\'eel temperature and an increasing saturation field. In sharp contrast, MnBi6Te10 experiences a phase transition from A-type AFM to a quasi-two-dimensional FM state with a suppressed saturation field under pressure. First-principles calculations reveal the essential role of intralayer exchange coupling from lattice compression in determining these magnetic properties. Such magnetic phase transition is also observed in 20% Sb-doped MnBi6Te10 due to the in-plane lattice compression.

cond-mat.mtrl-sci↗