arXiv subjects

Yu Zhang

Publications and source records attributed to Yu Zhang.

At least 667 records · Page 37Linked to original sources

arXiv2025

Spiral resonator referenced on-chip low noise microwave generation

In recent years, miniaturization and integration of photonic microwave oscillators by optical frequency division approach have witnessed rapid progress. In this work, we report on-chip low phase noise photonic microwave generation based on a planar chip design. Dual lasers are co-locked to a silicon nitride spiral resonator and their relative phase noise is measured below the cavity thermal noise limit, resulting in record low on-chip relative optical phase noise. A broadband integrated electro-optic comb up to 3.43 THz (27 nm) bandwidth is utilized to divide down the relative phase noise of the spiral resonator referenced lasers to the microwave domain. All-around record-low phase noise is achieved for planar chip-based photonic microwave oscillators from 10 Hz to 10 kHz offsets. The planar chip design, high technology-readiness level, foundry-ready processing, combined with the exceptional phase noise performance for our work represent a major advance of integrated photonic microwave oscillators.

physics.optics↗

arXiv2025

Noise May Contain Transferable Knowledge: Understanding Semi-supervised Heterogeneous Domain Adaptation from an Empirical Perspective

Semi-supervised heterogeneous domain adaptation (SHDA) addresses learning across domains with distinct feature representations and distributions, where source samples are labeled while most target samples are unlabeled, with only a small fraction labeled. Moreover, there is no one-to-one correspondence between source and target samples. Although various SHDA methods have been developed to tackle this problem, the nature of the knowledge transferred across heterogeneous domains remains unclear. This paper delves into this question from an empirical perspective. We conduct extensive experiments on about 330 SHDA tasks, employing two supervised learning methods and seven representative SHDA methods. Surprisingly, our observations indicate that both the category and feature information of source samples do not significantly impact the performance of the target domain. Additionally, noise drawn from simple distributions, when used as source samples, may contain transferable knowledge. Based on this insight, we perform a series of experiments to uncover the underlying principles of transferable knowledge in SHDA. Specifically, we design a unified Knowledge Transfer Framework (KTF) for SHDA. Based on the KTF, we find that the transferable knowledge in SHDA primarily stems from the transferability and discriminability of the source domain. Consequently, ensuring those properties in source samples, regardless of their origin (e.g., image, text, noise), can enhance the effectiveness of knowledge transfer in SHDA tasks. The codes and datasets are available at https://github.com/yyyaoyuan/SHDA.

cs.LG↗

arXiv2025

Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds

Discovering latent topics from text corpora has been studied for decades. Many existing topic models adopt a fully unsupervised setting, and their discovered topics may not cater to users' particular interests due to their inability of leveraging user guidance. Although there exist seed-guided topic discovery approaches that leverage user-provided seeds to discover topic-representative terms, they are less concerned with two factors: (1) the existence of out-of-vocabulary seeds and (2) the power of pre-trained language models (PLMs). In this paper, we generalize the task of seed-guided topic discovery to allow out-of-vocabulary seeds. We propose a novel framework, named SeeTopic, wherein the general knowledge of PLMs and the local semantics learned from the input corpus can mutually benefit each other. Experiments on three real datasets from different domains demonstrate the effectiveness of SeeTopic in terms of topic coherence, accuracy, and diversity.

cs.CL↗

arXiv2025

RM-PoT: Reformulating Mathematical Problems and Solving via Program of Thoughts

Recently, substantial advancements have been made in training language models to carry out step-by-step reasoning for solving intricate numerical reasoning tasks. Beyond the methods used to solve these problems, the structure and formulation of the problems themselves also play a crucial role in determining the performance of large language models. We observe that even small changes in the surface form of mathematical problems can have a profound impact on both the answer distribution and solve rate. This highlights the vulnerability of LLMs to surface-level variations, revealing its limited robustness when reasoning through complex problems. In this paper, we propose RM-PoT, a three-stage framework that integrates problem reformulation (RM), code-aided reasoning (PoT), and domain-aware few-shot learning to address these limitations. Our approach first reformulates the input problem into diverse surface forms to reduce structural bias, then retrieves five semantically aligned examples from a pre-constructed domain-specific question bank to provide contextual guidance, and finally generates executable Python code for precise computation.

cs.AI↗

arXiv2025

Chain-of-Factors Paper-Reviewer Matching

With the rapid increase in paper submissions to academic conferences, the need for automated and accurate paper-reviewer matching is more critical than ever. Previous efforts in this area have considered various factors to assess the relevance of a reviewer's expertise to a paper, such as the semantic similarity, shared topics, and citation connections between the paper and the reviewer's previous works. However, most of these studies focus on only one factor, resulting in an incomplete evaluation of the paper-reviewer relevance. To address this issue, we propose a unified model for paper-reviewer matching that jointly considers semantic, topic, and citation factors. To be specific, during training, we instruction-tune a contextualized language model shared across all factors to capture their commonalities and characteristics; during inference, we chain the three factors to enable step-by-step, coarse-to-fine search for qualified reviewers given a submission. Experiments on four datasets (one of which is newly contributed by us) spanning various fields such as machine learning, computer vision, information retrieval, and data mining consistently demonstrate the effectiveness of our proposed Chain-of-Factors model in comparison with state-of-the-art paper-reviewer matching methods and scientific pre-trained language models.

cs.IR↗

arXiv2025

Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation

In specialized fields like the scientific domain, constructing large-scale human-annotated datasets poses a significant challenge due to the need for domain expertise. Recent methods have employed large language models to generate synthetic queries, which serve as proxies for actual user queries. However, they lack control over the content generated, often resulting in incomplete coverage of academic concepts in documents. We introduce Concept Coverage-based Query set Generation (CCQGen) framework, designed to generate a set of queries with comprehensive coverage of the document's concepts. A key distinction of CCQGen is that it adaptively adjusts the generation process based on the previously generated queries. We identify concepts not sufficiently covered by previous queries, and leverage them as conditions for subsequent query generation. This approach guides each new query to complement the previous ones, aiding in a thorough understanding of the document. Extensive experiments demonstrate that CCQGen significantly enhances query quality and retrieval performance.

cs.IR↗

arXiv2025

Attosecond Inner-Shell Lasing at Angstrom Wavelengths

Since the invention of the laser nonlinear effects such as filamentation, Rabi-cycling and collective emission have been explored in the optical regime leading to a wide range of scientific and industrial applications. X-ray free electron lasers (XFELs) have led to the extension of many optical techniques to X-rays for their advantages of angstrom scale spatial resolution and elemental specificity. One such example is XFEL driven population inversion of 1s core hole states resulting in inner-shell K$α$ (2p to 1s) X-ray lasing in elements ranging from neon to copper, which has been utilized for nonlinear spectroscopy and development of next generation X-ray laser sources. Here we show that strong lasing effects, similar to those observed in the optical regime, can occur at 1.5 to 2.1 angstrom wavelengths during high intensity (> ${10^{19}}$ W/cm${^{2}}$) XFEL driven inner-shell lasing and superfluorescence of copper and manganese. Depending on the temporal substructure of the XFEL pump pulses(containing ${~10^{6}}$ - ${10^{8}}$ photons) i, the resulting inner-shell X-ray laser pulses can exhibit strong spatial inhomogeneities as well as spectral splitting, inhomogeneities and broadening. Through 3D Maxwell Bloch theory we show that the observed spatial inhomogeneities result from X-ray filamentation, and that the spectral splitting and broadening is driven by Rabi cycling with sub-femtosecond periods. Our simulations indicate that these X-ray pulses can have pulse lengths of less than 100 attoseconds and coherence properties that open the door for quantum X-ray optics applications.

physics.optics↗

arXiv2025

CP violation studies at Super Tau-Charm Facility

Charge-parity ($C\!P$) violation in the tau-charm energy region is a promising area for sensitive tests of Standard Model (SM) predictions and searches for new, beyond the SM physics. A future Tau-Charm Facility that operates at center-of-mass energies between 2.0 and 7.0 GeV, with a peak luminosity of $0.5\times10^{35}$~cm$^{-2}$s$^{-1}$, would provide huge numbers of hadrons and tau ($τ$) leptons that are produced in low-background environments and with well understood kinematic properties. In this report, prospects for unique studies of $C\!P$ violation in the decay of charmed hadrons, and in the production and decay of hyperons and $τ$ leptons at a next-generation tau-charm facility are discussed. In addition, opportunities for improved tests of $CPT$ invariance test in $K^{0}-\bar{K}^{0}$ mixing are presented.

hep-ex↗

arXiv2025

Diffusion Models for Computational Neuroimaging: A Survey

Computational neuroimaging involves analyzing brain images or signals to provide mechanistic insights and predictive tools for human cognition and behavior. While diffusion models have shown stability and high-quality generation in natural images, there is increasing interest in adapting them to analyze brain data for various neurological tasks such as data enhancement, disease diagnosis and brain decoding. This survey provides an overview of recent efforts to integrate diffusion models into computational neuroimaging. We begin by introducing the common neuroimaging data modalities, follow with the diffusion formulations and conditioning mechanisms. Then we discuss how the variations of the denoising starting point, condition input and generation target of diffusion models are developed and enhance specific neuroimaging tasks. For a comprehensive overview of the ongoing research, we provide a publicly available repository at https://github.com/JoeZhao527/dm4neuro.

cs.CV↗

arXiv2025

Thermodynamic modifications to Bardeen black holes surrounded by quintessence based on the new higher order GUP

In this article, the thermodynamic properties of Bardeen black holes surrounded by quintessence are investigated in the framework of a new higher order GUP. The modified Hawking temperature, entropy and heat capacity are derived using a heuristic approach. Meanwhile, the remnant temperature and mass are deduced, and the modified black hole state equation is obtained by utilizing the energy density of matter. Ultimately, we analyze the effects of the GUP controlling deformation parameter $β$ on these thermodynamic properties using graphical illustrations, to more comprehensively understand the thermodynamic behavior of the black hole in the context of higher order GUP.

gr-qc↗

arXiv2025

DEGAS: Detailed Expressions on Full-Body Gaussian Avatars

Although neural rendering has made significant advances in creating lifelike, animatable full-body and head avatars, incorporating detailed expressions into full-body avatars remains largely unexplored. We present DEGAS, the first 3D Gaussian Splatting (3DGS)-based modeling method for full-body avatars with rich facial expressions. Trained on multiview videos of a given subject, our method learns a conditional variational autoencoder that takes both the body motion and facial expression as driving signals to generate Gaussian maps in the UV layout. To drive the facial expressions, instead of the commonly used 3D Morphable Models (3DMMs) in 3D head avatars, we propose to adopt the expression latent space trained solely on 2D portrait images, bridging the gap between 2D talking faces and 3D avatars. Leveraging the rendering capability of 3DGS and the rich expressiveness of the expression latent space, the learned avatars can be reenacted to reproduce photorealistic rendering images with subtle and accurate facial expressions. Experiments on an existing dataset and our newly proposed dataset of full-body talking avatars demonstrate the efficacy of our method. We also propose an audio-driven extension of our method with the help of 2D talking faces, opening new possibilities for interactive AI agents.

cs.CV↗

arXiv2025

Three flavor QCD phase transition with Möbius domain wall fermions

We present an updated study of the $N_f=3$ QCD phase transition using Möbius domain wall fermions. Simulations were performed on $N_t=12$ lattices with aspect ratios ranging from 2 to 4 for various quark masses, at a lattice spacing of $a=0.1361(20)$ fm, corresponding to a temperature of 121(2) MeV. To clarify the nature of the phase transition, a large-volume lattice, $48^3 \times 12\times 16$, was added to analyze the volume dependence of disconnected chiral susceptibility. By examining the chiral condensate, disconnected chiral susceptibility, and Binder cumulant, and incorporating results from $24^3 \times 12 \times 16$ and $36^3 \times 12 \times 16$ lattices reported in earlier studies, we observe that the transition is consistent with a crossover at a quark mass of approximately $m_f^{\mathrm{\overline {MS}}}(2\, \mathrm{GeV}) \sim 4$ MeV at this temperature. Furthermore, we discuss the effects of residual chiral symmetry breaking on the chiral condensate and disconnected chiral susceptibility for different sizes in the 5th direction.

hep-lat↗

arXiv2025

DanModCap: Designing a Danmaku Moderation Tool for Video-Sharing Platforms that Leverages Impact Captions with Large Language Models

Online video platforms have gained increased popularity due to their ability to support information consumption and sharing and the diverse social interactions they afford. Danmaku, a real-time commentary feature that overlays user comments on a video, has been found to improve user engagement, however, the use of Danmaku can lead to toxic behaviors and inappropriate comments. To address these issues, we propose a proactive moderation approach inspired by Impact Captions, a visual technique used in East Asian variety shows. Impact Captions combine textual content and visual elements to construct emotional and cognitive resonance. Within the context of this work, Impact Captions were used to guide viewers towards positive Danmaku-related activities and elicit more pro-social behaviors. Leveraging Impact Captions, we developed DanModCap, an moderation tool that collected and analyzed Danmaku and used it as input to large generative language models to produce Impact Captions. Our evaluation of DanModCap demonstrated that Impact Captions reduced negative antagonistic emotions, increased users' desire to share positive content, and elicited self-control in Danmaku social action to fostering proactive community maintenance behaviors. Our approach highlights the benefits of using LLM-supported content moderation methods for proactive moderation in a large-scale live content contexts.

cs.HC↗

arXiv2025

Study of symmetries in finite temperature $N_f=2$ QCD with Möbius Domain Wall Fermions

We report on the ongoing study of symmetry of $N_f=2$ QCD around the critical temperature. Our simulations of $N_f = 2$ QCD employ the Möbius domain-wall fermion action with residual mass $\sim 1\mbox{MeV}$ or less, maintaining a good chiral symmetry. Using the screening masses from the two point spatial correlators we compare the mass difference between channels connected through various symmetry transformations. Our analysis focuses on restoration of the $SU(2)_L\times SU(2)_R$ as well as anomalously broken axial $U(1)_A$. We also present additional study of a potential $SU(2)_{CS}$ symmetry which may emerge at sufficiently high temperatures.

hep-lat↗

arXiv2025

EliGen: Entity-Level Controlled Image Generation with Regional Attention

Recent advancements in diffusion models have significantly advanced text-to-image generation, yet global text prompts alone remain insufficient for achieving fine-grained control over individual entities within an image. To address this limitation, we present EliGen, a novel framework for Entity-level controlled image Generation. Firstly, we put forward regional attention, a mechanism for diffusion transformers that requires no additional parameters, seamlessly integrating entity prompts and arbitrary-shaped spatial masks. By contributing a high-quality dataset with fine-grained spatial and semantic entity-level annotations, we train EliGen to achieve robust and accurate entity-level manipulation, surpassing existing methods in both spatial precision and image quality. Additionally, we propose an inpainting fusion pipeline, extending its capabilities to multi-entity image inpainting tasks. We further demonstrate its flexibility by integrating it with other open-source models such as IP-Adapter, In-Context LoRA and MLLM, unlocking new creative possibilities. The source code, model, and dataset are published at https://github.com/modelscope/DiffSynth-Studio.git.

cs.CV↗

arXiv2025

Beyond Prior Limits: Addressing Distribution Misalignment in Particle Filtering

Particle filtering is a Bayesian inference method and a fundamental tool in state estimation for dynamic systems, but its effectiveness is often limited by the constraints of the initial prior distribution, a phenomenon we define as the Prior Boundary Phenomenon. This challenge arises when target states lie outside the prior's support, rendering traditional particle filtering methods inadequate for accurate estimation. Although techniques like unbounded priors and larger particle sets have been proposed, they remain computationally prohibitive and lack adaptability in dynamic scenarios. To systematically overcome these limitations, we propose the Diffusion-Enhanced Particle Filtering Framework, which introduces three key innovations: adaptive diffusion through exploratory particles, entropy-driven regularisation to prevent weight collapse, and kernel-based perturbations for dynamic support expansion. These mechanisms collectively enable particle filtering to explore beyond prior boundaries, ensuring robust state estimation for out-of-boundary targets. Theoretical analysis and extensive experiments validate framework's effectiveness, indicating significant improvements in success rates and estimation accuracy across high-dimensional and non-convex scenarios.

stat.ML↗

arXiv2025

Long-lived sterile neutrinos from an axionlike particle at Belle II

Axionlike particles (ALPs) can be produced in meson decays via tree-level quark-flavor-violating couplings, and decay to a pair of sterile neutrinos if also coupled to them. Such light sterile neutrinos are necessarily long-lived and may give rise to striking signatures of displaced vertices (DVs) at terrestrial experiments. In this work, we study the prospect of the ongoing Belle II experiment for detecting the sterile neutrinos from the ALP, leveraging the $\mathcal{O}(10^{10})$ $B$-mesons projected to be produced at the experiment with an integrated luminosity of 50 ab$^{-1}$. We propose search strategies for one or two DVs, and perform Monte-Carlo simulations in order to estimate the sensitivity reach of Belle II to active-sterile-neutrino mixing $|V_{eN}|^2$ as functions of the sterile-neutrino mass. Signatures include a selected list of sterile-neutrino final states, for which we estimate an $\mathcal{O}(1)$ or lower background level. Our results show that the proposed search strategies can probe values of $|V_{eN}|^2$ up to about two orders of magnitude beyond the existing bounds, for ALP mass over 4 GeV and sterile-neutrino mass above the $D$-meson threshold. Compared to the one-DV search, the two-DV one, despite its weaker sensitivities as a result of double exponential suppression of the sterile-neutrino decay positions, possesses the advantage of possible full reconstruction of the signal event allowing for pinning down the masses of the sterile neutrino and the ALP, if a discovery is made.

hep-ph↗

arXiv2025

Searching for heavy neutral leptons coupled to axion-like particles at the LHC far detectors and SHiP

In hidden-sector models, axion-like particles (ALPs) can couple to heavy neutral leptons (HNLs), leading to rich phenomenologies. We study ALPs produced from $D$- and $B$-meson decays via quark-flavor-violating couplings, and decaying exclusively into a pair of HNLs which mix with active neutrinos. The ALP can be either short- or long-lived, depending on the masses of the ALP and the HNL, as well as the corresponding coupling strength. Such GeV-scale HNLs are necessarily long-lived given the current bounds on their mixing parameters. We assess the sensitivities of the LHC far detectors and SHiP, to the long-lived HNLs in such theoretical scenarios. We find that for currently allowed values of the ALP couplings, most of these experiments can probe the active-sterile-neutrino mixing parameters multiple orders of magnitude beyond the present bounds, covering large parameter region targeted with the type-I seesaw mechanism. In addition, our results show that compared to the case of a promptly decaying ALP, assuming an ALP of longer lifetimes weakens the sensitivities of the considered experiments to the long-lived HNLs.

hep-ph↗