Tootfinder

Airalogy: AI-empowered universal data digitization for research automation
Zijie Yang, Qiji Zhou, Fang Guo, Sijie Zhang, Yexun Xi, Jinglei Nie, Yudian Zhu, Liping Huang, Chou Wu, Yonghe Xia, Xiaoyu Ma, Yingming Pu, Panzhong Lu, Junshu Pan, Mingtao Chen, Tiannan Guo, Yanmei Dou, Hongyu Chen, Anping Zeng, Jiaxing Huang, Tian Xu, Yue Zhang
https://

Airalogy: AI-empowered universal data digitization for research automation
Research data are the foundation of Artificial Intelligence (AI)-driven science, yet current AI applications remain limited to a few fields with readily available, well-structured, digitized datasets. Achieving comprehensive AI empowerment across multiple disciplines is still out of reach. Present-day research data collection is often fragmented, lacking unified standards, inefficiently managed, and difficult to share. Creating a single platform for standardized data digitization needs to overc…

Gov. Greg Abbott vetoes THC ban, calls for regulation instead (Kayla Guo/The Texas Tribune)
https://www.texastribune.org/2025/06/22/texas-thc-ban-bill-greg-abbott-veto-senate-bill-3/
http://www.memeorandum.com/250623/p15#a250623p15

EarthLink: Interpreting Climate Signals with Self-Evolving AI Agents
Zijie Guo, Jiong Wang, Xiaoyu Yue, Wangxu Wei, Zhe Jiang, Wanghan Xu, Ben Fei, Wenlong Zhang, Xinyu Gu, Lijing Cheng, Jing-Jia Luo, Chao Li, Yaqiang Wang, Tao Chen, Wanli Ouyang, Fenghua Ling, Lei Bai
https://arxiv.org/abs/2507.17311

EarthLink: Interpreting Climate Signals with Self-Evolving AI Agents
Modern Earth science is at an inflection point. The vast, fragmented, and complex nature of Earth system data, coupled with increasingly sophisticated analytical demands, creates a significant bottleneck for rapid scientific discovery. Here we introduce EarthLink, the first AI agent designed as an interactive copilot for Earth scientists. It automates the end-to-end research workflow, from planning and code generation to multi-scenario analysis. Unlike static diagnostic tools, EarthLink can lea…

Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
Ang Li, Charles Wang, Kaiyu Yue, Zikui Cai, Ollie Liu, Deqing Fu, Peng Guo, Wang Bill Zhu, Vatsal Sharan, Robin Jia, Willie Neiswanger, Furong Huang, Tom Goldstein, Micah Goldblum
https://arxiv.org/abs/2507.16746

Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
Humans often use visual aids, for example diagrams or sketches, when solving complex problems. Training multimodal models to do the same, known as Visual Chain of Thought (Visual CoT), is challenging due to: (1) poor off-the-shelf visual CoT performance, which hinders reinforcement learning, and (2) the lack of high-quality visual CoT training data. We introduce $\textbf{Zebra-CoT}$, a diverse large-scale dataset with 182,384 samples, containing logically coherent interleaved text-image reasoni…

$La_3Pd_2NaO_9$: A High-Valent Insulating Palladate
Qingqing Yang, Ning Guo, Tieyan Chang, Zheng Guo, Xiaoli Wang, Chuanyan Fan, Chao Liu, Lu Han, Feiyu Li, Tao He, Qiang Zheng, Yu-Sheng Chen, Junjie Zhang
https://arxiv.org/abs/2506.15966

$La_3Pd_2NaO_9$: A High-Valent Insulating Palladate
A high-valent palladate, $La_3Pd_2NaO_9$, has been synthesized for the first time. Single crystals with dimensions of 20 $μ$m on edge were successfully grown using the flux method at 420 $^o$C and 70 bar oxygen pressure. Energy dispersive spectroscopy (EDS) and inductively coupled plasma mass spectroscopy (ICP) measurements show that the atomic ratio of La: (Pd+Na) is 3: 3 and Pd: Na is 2: 1. X-ray photoelectron spectroscopy (XPS) measurements show that the oxidation state of Pd is dominated b…

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
Shanghai AI Lab, :, Xiaoyang Chen, Yunhao Chen, Zeren Chen, Zhiyun Chen, Hanyun Cui, Yawen Duan, Jiaxuan Guo, Qi Guo, Xuhao Hu, Hong Huang, Lige Huang, Chunxiao Li, Juncheng Li, Qihao Lin, Dongrui Liu, Xinmin Liu, Zicheng Liu, Chaochao Lu, Xiaoya Lu, Jingjing Qu, Qibing Ren, Jing Shao, Jingwei Shi, Jingwei Sun, Peng Wang, Weibing Wang, Jia Xu, Lewen Yan, Xiao Yu, Yi Yu, Boxuan Zhang, Jie Zhang, Weichen…

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier risks. Drawing on the E-T-C analysis (deployment environment, threat source, enabling capability) from the Frontier AI Risk Management Framework (v1.0) (SafeWork-F1-Framework), we identify critical risks in seven areas: cyber offense, biological and chemical risks, persuasion and manipulation, uncontrolled autonomous…

SVAgent: AI Agent for Hardware Security Verification Assertion
Rui Guo, Avinash Ayalasomayajula, Henian Li, Jingbo Zhou, Sujan Kumar Saha, Farimah Farahmandi
https://arxiv.org/abs/2507.16203

SVAgent: AI Agent for Hardware Security Verification Assertion
Verification using SystemVerilog assertions (SVA) is one of the most popular methods for detecting circuit design vulnerabilities. However, with the globalization of integrated circuit design and the continuous upgrading of security requirements, the SVA development model has exposed major limitations. It is not only inefficient in development, but also unable to effectively deal with the increasing number of security vulnerabilities in modern complex integrated circuits. In response to these c…

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
Teng Guo, Baichuan Huang, Jingjin Yu
https://arxiv.org/abs/2506.17110 https://

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
Accurate 6D object pose estimation is a prerequisite for successfully completing robotic prehensile and non-prehensile manipulation tasks. At present, 6D pose estimation for robotic manipulation generally relies on depth sensors based on, e.g., structured light, time-of-flight, and stereo-vision, which can be expensive, produce noisy output (as compared with RGB cameras), and fail to handle transparent objects. On the other hand, state-of-the-art monocular depth estimation models (MDEMs) provid…

Encrypted-State Quantum Compilation Scheme Based on Quantum Circuit Obfuscation
Chenyi Zhang, Tao Shang, Xueyi Guo
https://arxiv.org/abs/2507.17589 https://

Encrypted-State Quantum Compilation Scheme Based on Quantum Circuit Obfuscation
With the rapid advancement of quantum computing, quantum compilation has become a crucial layer connecting high-level algorithms with physical hardware. In quantum cloud computing, compilation is performed on the cloud side, which exposes user circuits to potential risks such as structural leakage and output predictability. To address these issues, we propose the encrypted-state quantum compilation scheme based on quantum circuit obfuscation (ECQCO), the first secure compilation framework tailo…

Investigating Training Data Detection in AI Coders
Tianlin Li, Yunxiang Wei, Zhiming Li, Aishan Liu, Qing Guo, Xianglong Liu, Dongning Sun, Yang Liu
https://arxiv.org/abs/2507.17389

Investigating Training Data Detection in AI Coders
Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these models occasionally produce outputs that contain proprietary or sensitive code snippets, raising concerns about potential non-compliant use of training data, and posing risks to privacy and intellectual property. To ensure responsible and compliant deployment of CodeLLMs, training data detection (TDD) has become a critical task. While recent TDD methods have…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[3/3]:
- Deep Video Discovery: Agentic Search with Tool Use for Long-form Video Understanding
Xiaoyi Zhang, Zhaoyang Jia, Zongyu Guo, Jiahao Li, Bin Li, Houqiang Li, Yan Lu

PPTP: Performance-Guided Physiological Signal-Based Trust Prediction in Human-Robot Collaboration
Hao Guo, Wei Fan, Shaohui Liu, Feng Jiang, Chunzhi Yi
https://arxiv.org/abs/2506.16677

PPTP: Performance-Guided Physiological Signal-Based Trust Prediction in Human-Robot Collaboration
Trust prediction is a key issue in human-robot collaboration, especially in construction scenarios where maintaining appropriate trust calibration is critical for safety and efficiency. This paper introduces the Performance-guided Physiological signal-based Trust Prediction (PPTP), a novel framework designed to improve trust assessment. We designed a human-robot construction scenario with three difficulty levels to induce different trust states. Our approach integrates synchronized multimodal p…

Using Machine Learning in Analyzing Air Quality Discrepancies of Environmental Impact
Shuangbao Paul Wang, Lucas Yang, Rahouane Chouchane, Jin Guo, Michael Bailey
https://arxiv.org/abs/2506.17319

Using Machine Learning in Analyzing Air Quality Discrepancies of Environmental Impact
In this study, we apply machine learning and software engineering in analyzing air pollution levels in City of Baltimore. The data model was fed with three primary data sources: 1) a biased method of estimating insurance risk used by homeowners loan corporation, 2) demographics of Baltimore residents, and 3) census data estimate of NO2 and PM2.5 concentrations. The dataset covers 650,643 Baltimore residents in 44.7 million residents in 202 major cities in US. The results show that air pollution…

Regular Tree Search for Simulation Optimization
Du-Yi Wang, Guo Liang, Guangwu Liu, Kun Zhang
https://arxiv.org/abs/2506.17696 https://

Regular Tree Search for Simulation Optimization
Tackling simulation optimization problems with non-convex objective functions remains a fundamental challenge in operations research. In this paper, we propose a class of random search algorithms, called Regular Tree Search, which integrates adaptive sampling with recursive partitioning of the search space. The algorithm concentrates simulations on increasingly promising regions by iteratively refining a tree structure. A tree search strategy guides sampling decisions, while partitioning is tri…

A High Magnifications Histopathology Image Dataset for Oral Squamous Cell Carcinoma Diagnosis and Prognosis
Jinquan Guan, Junhong Guo, Qi Chen, Jian Chen, Yongkang Cai, Yilin He, Zhiquan Huang, Yan Wang, Yutong Xie
https://arxiv.org/abs/2507.16360

A High Magnifications Histopathology Image Dataset for Oral Squamous Cell Carcinoma Diagnosis and Prognosis
Oral Squamous Cell Carcinoma (OSCC) is a prevalent and aggressive malignancy where deep learning-based computer-aided diagnosis and prognosis can enhance clinical assessments.However, existing publicly available OSCC datasets often suffer from limited patient cohorts and a restricted focus on either diagnostic or prognostic tasks, limiting the development of comprehensive and generalizable models. To bridge this gap, we introduce Multi-OSCC, a new histopathology image dataset comprising 1,325 O…

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
Senyao Li, Haozhao Wang, Wenchao Xu, Rui Zhang, Song Guo, Jingling Yuan, Xian Zhong, Tianwei Zhang, Ruixuan Li
https://arxiv.org/abs/2507.16731

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
As large language models (LLMs) evolve, deploying them solely in the cloud or compressing them for edge devices has become inadequate due to concerns about latency, privacy, cost, and personalization. This survey explores a collaborative paradigm in which cloud-based LLMs and edge-deployed small language models (SLMs) cooperate across both inference and training. We present a unified taxonomy of edge-cloud collaboration strategies. For inference, we categorize approaches into task assignment, t…

The investigation of 84 TESS totally eclipsing contact binaries
Yani Guo, Kai Li, Liheng Wang, Qiqi Xia, Xiang Gao, Jingran Xu, Jingyi Wang
https://arxiv.org/abs/2506.15989

The investigation of 84 TESS totally eclipsing contact binaries
Based on the eclipsing binary catalog provided by \cite{2022ApJS..258...16P}, 84 totally eclipsing contact binaries with stable light curves were selected. The TESS light curves of these 84 targets were studied using the Physics Of Eclipsing Binaries code. The results indicate that there are 18 deep contact binaries, 39 moderate contact binaries, and 27 shallow contact binaries. Among them, 43 targets exhibit the O'Connell effect, which is attributed to the presence of star-spot on the componen…

CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
Junze Chen, Xinjie Yang, Cheng Yang, Junfei Bao, Zeyuan Guo, Yawen Li, Chuan Shi
https://arxiv.org/abs/2506.17281

CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
Recommender systems (RSs) are designed to retrieve candidate items a user might be interested in from a large pool. A common approach is using graph neural networks (GNNs) to capture high-order interaction relationships. As large language models (LLMs) have shown strong capabilities across domains, researchers are exploring their use to enhance recommendation. However, prior work limits LLMs to re-ranking results or dataset augmentation, failing to utilize their power during candidate filtering…

Modeling and Analysis of Land-to-Ship Maritime Wireless Channels at 5.8 GHz
Shu Sun, Yulu Guo, Meixia Tao, Wei Feng, Jun Chen, Ruifeng Gao, Ye Li, Jue Wang, Theodore S. Rappaport
https://arxiv.org/abs/2507.15969

Modeling and Analysis of Land-to-Ship Maritime Wireless Channels at 5.8 GHz
Maritime channel modeling is crucial for designing robust communication systems in marine environments, where factors like waves and wind impact signal propagation. This article investigates land-to-ship maritime wireless channel characteristics at 5.8 GHz based upon an extensive measurement campaign, with concurrent hydrological and meteorological information collection. First, a novel large-scale path loss model with physical foundation and high accuracy is proposed for dynamic marine environ…

MTU: The Multifunction Tree Unit in zkSpeed for Accelerating HyperPlonk
Jianqiao Mo, Alhad Daftardar, Joey Ah-kiow, Kaiyue Guo, Benedikt B\"unz, Siddharth Garg, Brandon Reagen
https://arxiv.org/abs/2507.16793

MTU: The Multifunction Tree Unit in zkSpeed for Accelerating HyperPlonk
Zero-Knowledge Proofs (ZKPs) are critical for privacy preservation and verifiable computation. Many ZKPs rely on kernels such as the SumCheck protocol and Merkle Tree commitments, which enable their security properties. These kernels exhibit balanced binary tree computational patterns, which enable efficient hardware acceleration. Prior work has investigated accelerating these kernels as part of an overarching ZKP protocol; however, a focused study of how to best exploit the underlying tree pat…

Parallel (co-)tractors and the geometry of first BGG solutions on almost Grassmannian structures
Zhangwen Guo
https://arxiv.org/abs/2507.17605 https://arxi…

Parallel (co-)tractors and the geometry of first BGG solutions on almost Grassmannian structures
We study the standard tractor bundle and the standard cotractor bundle of an almost Grassmann structure: We provide explicit formulae for their splitting operators, first BGG operators as well as prolongation connections. We characterize parallel tractors and cotractors as well as the solutions of the BGG operators in standard geometric terms. Moreover, we describe the geometry canonically endowed on the zero locus of a solution of the first BGG operators.

Flavor SU(3) analysis of the charmless semileptonic $B \to PV\ell^ \nu_\ell$ decays
Yi Qiao, Jin-Huan Sheng, Yuan-Guo Xu, Ru-Min Wang
https://arxiv.org/abs/2507.17537

Flavor SU(3) analysis of the charmless semileptonic $B \to PV\ell^+ν_\ell$ decays
All charmless $B \to PV\ell^+ν_\ell$ ($P$ denotes light pseudoscalar meson and $V$ denotes vector meson) decays have not been experimentally observed to date, but some of them might be measured in the near future. The charmless $B \to PV\ell^+ν_\ell$ decays with the axial-vector ($A$) resonance states, the tensor ($T$) resonance states and the excited vector ($V_{E,D}$) resonance states are studied based on flavor SU(3) analysis in this work, where $V_E$ contains $\{ρ(1450), K^*(1410), ω(14…

HybHuff: Lossless Compression for Hypergraphs via Entropy-Guided Huffman-Bitwise Coordination
Tianyu Zhao, Dongfang Zhao, Luanzheng Guo, Nathan Tallent
https://arxiv.org/abs/2506.15844

HybHuff: Lossless Compression for Hypergraphs via Entropy-Guided Huffman-Bitwise Coordination
Hypergraphs provide a natural representation for many-to-many relationships in data-intensive applications, yet their scalability is often hindered by high memory consumption. While prior work has improved computational efficiency, reducing the space overhead of hypergraph representations remains a major challenge. This paper presents a hybrid compression framework for integer-based hypergraph adjacency formats, which adaptively combines Huffman encoding and bitwise encoding to exploit structur…

A $6.37\,{\rm Hz}$ quasi-periodic oscillating photospheric emission in GRB~240825A
Guo-Yu Li, Da-Bin Lin, Zhi-Lin Chen, Bao-Quan Huang, Tong Liu, En-Wei Liang
https://arxiv.org/abs/2507.16538

A $6.37\,{\rm Hz}$ quasi-periodic oscillating photospheric emission in GRB~240825A
Using data from Swift-BAT and Fermi-GBM, we report the first detection of a high-confidence quasi-periodic oscillation (QPO) in the thermal emission of gamma-ray burst GRB~240825A. The spectral analysis of the burst reveals two radiation components, including a thermal emission dominant in $100 \text{--} 300\,\mathrm{keV}$ and a non-thermal emission spanning a wide energy range. During the interval $2.07 \text{--} 3.25\,\mathrm{s}$ post-trigger, a strong QPO signal at $6.37\,\mathrm{Hz}$ ($\gtr…

Cosmological Preference for a Positive Neutrino Mass at 2.7$\sigma$: A Joint Analysis of DESI DR2, DESY5, and DESY1 Data
Guo-Hong Du, Tian-Nuo Li, Peng-Ju Wu, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2507.16589

Cosmological Preference for a Positive Neutrino Mass at 2.7$σ$: A Joint Analysis of DESI DR2, DESY5, and DESY1 Data
Neutrinos and dark energy (DE) have entered a new era of investigation, as the latest DESI baryon acoustic oscillation measurements tighten the constraints on the neutrino mass and suggest that DE may be dynamical rather than a cosmological constant. In this work, we investigate the cosmological implications of simultaneously incorporating $\sum m_ν$ and $N_{\rm eff}$ within the framework of dynamical DE. A joint analysis of DESI DR2, cosmic microwave background, DESY5 supernova, and DESY1 wea…

Empowering Iterative Graph Alignment Using Heat Diffusion
Boyan Wang, Weijie Feng, Jinyang Huang, Dan Guo, Zhi Liu
https://arxiv.org/abs/2506.17640 https:/…

Empowering Iterative Graph Alignment Using Heat Diffusion
Unsupervised plain graph alignment (UPGA) aims to align corresponding nodes across two graphs without any auxiliary information. Existing UPGA methods rely on structural consistency while neglecting the inherent structural differences in real-world graphs, leading to biased node representations. Moreover, their one-shot alignment strategies lack mechanisms to correct erroneous matches arising from inaccurate anchor seeds. To address these issues, this paper proposes IterAlign, a novel parameter…

An FDM-sFEM scheme on time-space manifolds and its superconvergence analysis
Chengrun Jiang, Guozhi Dong, Hailong Guo, Zuoqiang Shi
https://arxiv.org/abs/2507.17378 https://

An FDM-sFEM scheme on time-space manifolds and its superconvergence analysis
We study superconvergent discretization of the Laplace-Beltrami operator on time-space product manifolds with Neumann temporal boundary values, which arise in the context of dynamic optimal transport on general surfaces. We propose a coupled scheme that combines finite difference methods in time with surface finite element methods in space. By establishing a new summation by parts formula and proving the supercloseness of the semi-discrete solution, we derive superconvergence results for the re…

Analysis of a three-dimensional rapidly rotating convection model without thermal diffusion
Chongsheng Cao, Yanqiu Guo, Edriss S. Titi
https://arxiv.org/abs/2507.16143

Analysis of a three-dimensional rapidly rotating convection model without thermal diffusion
We study a three-dimensional rapidly rotating convection model featuring tall columnar structures, in the absence of thermal diffusion. We establish the global existence and uniqueness of weak solutions, as well as the Hadamard well-posedness of global strong solutions to this model. The lack of thermal diffusion introduces significant challenges in the analysis. To overcome these challenges, we first investigate the regularized model with thermal diffusion and establish delicate estimates that…

Collective synchrony in confluent, pulsatile epithelia
Wenhui Tang, Mehrana R. Nejad, Adrian F. Pegoraro, L. Mahadevan, Ming Guo
https://arxiv.org/abs/2507.16772

Collective synchrony in confluent, pulsatile epithelia
Collective cell migration lies at the intersection of developmental biology and non-equilibrium physics, where active processes give rise to emergent patterns that are biologically relevant. Here, we investigate dilatational modes--cycles of expansion and contraction--in epithelial monolayers, and show that the divergence of the velocity field exhibits robust, large-scale temporal oscillations. These oscillatory patterns, reminiscent of excitable media and their biological analogs, emerge spont…

Triadic Novelty: A Typology and Measurement Framework for Recognizing Novel Contributions in Science
Jin Ai, Richard S. Steinberg, Chao Guo, Filipi Nascimento Silva
https://arxiv.org/abs/2506.17851

Triadic Novelty: A Typology and Measurement Framework for Recognizing Novel Contributions in Science
Scientific progress depends on novel ideas, but current reward systems often fail to recognize them. Many existing metrics conflate novelty with popularity, privileging ideas that fit existing paradigms over those that challenge them. This study develops a theory-driven framework to better understand how different types of novelty emerge, take hold, and receive recognition. Drawing on network science and theories of discovery, we introduce a triadic typology: Pioneers, who introduce entirely ne…

Graphics4Science: Computer Graphics for Scientific Impacts
Peter Yichen Chen, Minghao Guo, Hanspeter Pfister, Ming Lin, William Freeman, Qixing Huang, Han-Wei Shen, Wojciech Matusik
https://arxiv.org/abs/2506.15786

Graphics4Science: Computer Graphics for Scientific Impacts
Computer graphics, often associated with films, games, and visual effects, has long been a powerful tool for addressing scientific challenges--from its origins in 3D visualization for medical imaging to its role in modern computational modeling and simulation. This course explores the deep and evolving relationship between computer graphics and science, highlighting past achievements, ongoing contributions, and open questions that remain. We show how core methods, such as geometric reasoning an…

Fully analog end-to-end online training with real-time adaptibility on integrated photonic platform
Zhimu Guo, A. Aadhi, Adam N. McCaughan, Alexander N. Tait, Nathan Youngblood, Sonia M. Buckley, Bhavin J. Shastri
https://arxiv.org/abs/2506.18041

Fully analog end-to-end online training with real-time adaptibility on integrated photonic platform
Analog neuromorphic photonic processors are uniquely positioned to harness the ultrafast bandwidth and inherent parallelism of light, enabling scalability, on-chip integration and significant improvement in computational performance. However, major challenges remain unresolved especially in achieving real-time online training, efficient end-to-end anolog systems, and adaptive learning for dynamical environmental changes. Here, we demonstrate an on-chip photonic analog end-to-end adaptive learni…

SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
Yi Guo, Wei Wang, Zhihang Yuan, Rong Cao, Kuan Chen, Zhengyang Chen, Yuanyuan Huo, Yang Zhang, Yuping Wang, Shouda Liu, Yuxuan Wang
https://arxiv.org/abs/2507.16884

SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
Generative models like Flow Matching have achieved state-of-the-art performance but are often hindered by a computationally expensive iterative sampling process. To address this, recent work has focused on few-step or one-step generation by learning the average velocity field, which directly maps noise to data. MeanFlow, a leading method in this area, learns this field by enforcing a differential identity that connects the average and instantaneous velocities. In this work, we argue that this d…

Replaced article(s) found for cs.MM. https://arxiv.org/list/cs.MM/new
[1/1]:
- Music-Aligned Holistic 3D Dance Generation via Hierarchical Motion Modeling
Xiaojie Li, Ronghui Li, Shukai Fang, Shuzhao Xie, Xiaoyang Guo, Jiaqing Zhou, Junkun Peng, Zhi Wang

Role of nuclear and electromagnetic fragmentation in the charge-changing reactions of 18O on carbon and lead targets at around 370 MeV/nucleon
J. R. Liu, B. -H. Sun, J. W. Zhao, G. Guo, G. S. Li, Z. Z. Li, Y. F. Niu, I. Tanihata, S. Terashima, F. Wang, M. Wang, X. L. Wei, J. Y. Xu, J. C. Zhang, L. H. Zhu, L. C. He, C. Y. Liu, C. G. Lu, W. J. Lin, W. P. Lin, Z. Liu, P. P. Ren, Y. Z. Sun, Z. Y. Sun, J. Wang, S. T. Wang, X. D. Xu, M. X. Zhang, X. H. Zhang, Y. Zhang

Role of nuclear and electromagnetic fragmentation in the charge-changing reactions of 18O on carbon and lead targets at around 370 MeV/nucleon
Charge-changing cross sections (CCCSs) of 18O on carbon (C) and lead (Pb) targets have been measured with an uncertainty of less than 4% at around 370MeV/nucleon. We evaluate the contributions of nucleon-nucleon (NN) and electromagnetic (EM) interactions to CCCSs by considering the direct proton removal process, the charged particle evaporation (CPE) after neutron removal, and the EM excitation. We conclude that the CPE accounts for 12.3% and 5% of CCCSs on C and Pb, respectively. Only less tha…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/5]:
- Unsupervised Joint Learning of Optical Flow and Intensity with Event Cameras
Shuang Guo, Friedhelm Hamann, Guillermo Gallego

Replaced article(s) found for q-fin.ST. https://arxiv.org/list/q-fin.ST/new
[1/1]:
- Joint News, Attention Spillover,and Market Returns
Li Guo, Lin Peng, Yubo Tao, Jun Tu

Improvement on LiDAR-Camera Calibration Using Square Targets
Zhongyuan Li, Honggang Gou, Ping Li, Jiaotong Guo, Mao Ye
https://arxiv.org/abs/2506.18294 htt…

Improvement on LiDAR-Camera Calibration Using Square Targets
Precise sensor calibration is critical for autonomous vehicles as a prerequisite for perception algorithms to function properly. Rotation error of one degree can translate to position error of meters in target object detection at large distance, leading to improper reaction of the system or even safety related issues. Many methods for multi-sensor calibration have been proposed. However, there are very few work that comprehensively consider the challenges of the calibration procedure when appli…

Quantum teleportation of an elemental silicon nanophotonic CNOT gate
Kai-Chi Chang, Xiang Cheng, Felix Ribuot-Hirsch, Murat Can Sarihan, Yujie Chen, Jaime Gonzalo Flor Flores, Mingbin Yu, Patrick Guo-Qiang Lo, Dim-Lee Kwong, Chee Wei Wong
https://arxiv.org/abs/2507.16783

Quantum teleportation of an elemental silicon nanophotonic CNOT gate
Large-scale quantum computers possess the capacity to effectively tackle practical problems that can be insurmountable for classical computers. The main challenge in building these quantum computers is to realize scalable modules for remote qubits and entanglement. By assembling small, specialized parts into a larger architecture, the modular approach mitigates complexity and uncertainty. Such a distributed architecture requires non-local quantum gate operations between remote qubits. An essent…

Tracing Errors, Constructing Fixes: Repository-Level Memory Error Repair via Typestate-Guided Context Retrieval
Xiao Cheng, Zhihao Guo, Huan Huo, Yulei Sui
https://arxiv.org/abs/2506.18394

Tracing Errors, Constructing Fixes: Repository-Level Memory Error Repair via Typestate-Guided Context Retrieval
Memory-related errors in C programming continue to pose significant challenges in software development, primarily due to the complexities of manual memory management inherent in the language. These errors frequently serve as vectors for severe vulnerabilities, while their repair requires extensive knowledge of program logic and C's memory model. Automated Program Repair (APR) has emerged as a critical research area to address these challenges. Traditional APR approaches rely on expert-designed …

V-CASS: Vision-context-aware Expressive Speech Synthesis for Enhancing User Understanding of Videos
Qixin Wang, Songtao Zhou, Zeyu Jin, Chenglin Guo, Shikun Sun, Xiaoyu Qin
https://arxiv.org/abs/2506.16716

V-CASS: Vision-context-aware Expressive Speech Synthesis for Enhancing User Understanding of Videos
Automatic video commentary systems are widely used on multimedia social media platforms to extract factual information about video content. However, current systems may overlook essential para-linguistic cues, including emotion and attitude, which are critical for fully conveying the meaning of visual content. The absence of these cues can limit user understanding or, in some cases, distort the video's original intent. Expressive speech effectively conveys these cues and enhances the user's com…

On weighted multilinear polynomial averages in finite fields
Guo-Dong Hong
https://arxiv.org/abs/2507.14414 https://arxiv.org/pdf/250…

On weighted multilinear polynomial averages in finite fields
We study the weighted multilinear polynomial averages in finite fields. The essential ingredient is the $u^s$-norm control of the corresponding weighted multilinear polynomial averages in finite fields, which is motivated by Teräväinen \cite{T24}. As an application, we prove an asymptotic formula for the number of the following multidimensional rational function progressions in the subsets of $\mathbb{F}_p^D$: \[ \textbf{x}, \textbf{x}+ P_1(φ(y))v_1,\cdots, \textbf{x}+ P_k(φ(y))v_k, \] wher…

Replaced article(s) found for math.KT. https://arxiv.org/list/math.KT/new
[1/1]:
- Hilbert-Hadamard spaces and the equivariant coarse Novikov conjecture
Liang Guo, Qin Wang, Jianchao Wu, Guoliang Yu

Replaced article(s) found for physics.app-ph. https://arxiv.org/list/physics.app-ph/new
[1/1]:
- A Programmable and High-Precision Micro-Transfer Printing Platform for Multi-Material, Heterogene...
Guo, Yang, Gan, Zhang, Zhang, Jiang, Lin, Chen, Zhang, Wang
…

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model
Zhe Xu, Ziyi Liu, Junlin Hou, Jiabo Ma, Cheng Jin, Yihui Wang, Zhixuan Chen, Zhengyu Zhang, Zhengrui Guo, Fengtao Zhou, Yingxue Xu, Xi Wang, Ronald Cheong Kin Chan, Li Liang, Hao Chen
https://arxiv.org/abs/2507.17303

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model
Multimodal large language models (MLLMs) have emerged as powerful tools for computational pathology, offering unprecedented opportunities to integrate pathological images with language context for comprehensive diagnostic analysis. These models hold particular promise for automating complex tasks that traditionally require expert interpretation of pathologists. However, current MLLM approaches in pathology demonstrate significantly constrained reasoning capabilities, primarily due to their reli…

Replaced article(s) found for eess.AS. https://arxiv.org/list/eess.AS/new
[1/1]:
- ISDrama: Immersive Spatial Drama Generation through Multimodal Prompting
Yu Zhang, Wenxiang Guo, Changhao Pan, Zhiyuan Zhu, Tao Jin, Zhou Zhao

Strategyproofness and Monotone Allocation of Auction in Social Networks
Yuhang Guo, Dong Hao, Bin Li, Mingyu Xiao, Bakh Khoussainov
https://arxiv.org/abs/2507.14472

Strategyproofness and Monotone Allocation of Auction in Social Networks
Strategyproofness in network auctions requires that bidders not only report their valuations truthfully, but also do their best to invite neighbours from the social network. In contrast to canonical auctions, where the value-monotone allocation in Myerson's Lemma is a cornerstone, a general principle of allocation rules for strategyproof network auctions is still missing. We show that, due to the absence of such a principle, even extensions to multi-unit network auctions with single-unit demand…

A Tractable Approach to Massive Communication and Ubiquitous Connectivity in 6G Standardization
Junyi Jiang (Angela), Wei Chen (Angela), Xin Guo (Angela), Shenghui Song (Angela), Ying Jun (Angela), Zhang, Zhu Han, Merouane Debbah, Khaled B. Letaief
https://arxiv.org/abs/2506.16304

A Tractable Approach to Massive Communication and Ubiquitous Connectivity in 6G Standardization
The full-scale 6G standardization has attracted considerable recent attention, especially since the first 3GPP-wide 6G workshop held in March 2025. To understand the practical and fundamental values of 6G and facilitate its standardization, it is crucial to explore the theoretical limits of spectrum, energy, and coverage efficiency considering practical hardware and signaling constraints. In this paper, we present a mean-field-approximation-based investigation on two out of six use case scenari…

Exploring the properties of newborn pulsars with high-energy neutrinos
Zi-Zhuo Xiao, Gang Guo, Tuohuniyazi Tuniyazi
https://arxiv.org/abs/2507.16551 https:…

Exploring the properties of newborn pulsars with high-energy neutrinos
Newborn pulsars resulting from core-collapse supernovae (CCSNe) are promising sources of high-energy (HE) cosmic rays and neutrinos. In this work, we focus on HE neutrinos generated by interactions between protons accelerated in relativistic pulsar winds and SN ejecta. Using a binned likelihood analysis, we evaluate the detection prospects of these neutrinos with IceCube and explore their potential for probing the initial spin period ($P$) and magnetic field strength ($B$) of newborn pulsars. N…

A direct method in noncommutative integrable systems
Shi-Hao Li, Shou-Feng Shen, Guo-Fu Yu, Jun-Yang Zhang
https://arxiv.org/abs/2506.18661 https://…

A direct method in noncommutative integrable systems
We present a constructive framework for deriving noncommutative (NC) integrable equations directly from quasi-determinant solutions. Building upon the quasi-Wronskian structure, we extend the classical direct method to the NC setting, where standard determinant identities are replaced by algebraic relations intrinsic to quasi-determinants. By analyzing derivative identities satisfied by quasi-determinants, we recover the NC Kadomtsev-Petviashvili (ncKP) and Date-Jimbo-Kashiwara-Miwa (ncDJKM) eq…

Expert-Guided LLM Reasoning for Battery Discovery: From AI-Driven Hypothesis to Synthesis and Characterization
Shengchao Liu, Hannan Xu, Yan Ai, Huanxin Li, Yoshua Bengio, Harry Guo
https://arxiv.org/abs/2507.16110

Expert-Guided LLM Reasoning for Battery Discovery: From AI-Driven Hypothesis to Synthesis and Characterization
Large language models (LLMs) leverage chain-of-thought (CoT) techniques to tackle complex problems, representing a transformative breakthrough in artificial intelligence (AI). However, their reasoning capabilities have primarily been demonstrated in solving math and coding problems, leaving their potential for domain-specific applications-such as battery discovery-largely unexplored. Inspired by the idea that reasoning mirrors a form of guided search, we introduce ChatBattery, a novel agentic f…

Exploring the neutron-star matter properties via the deformed nuclear reactions
Yuan-Qing Guo, Ya-Peng Zhang, Zhao-Qing Feng
https://arxiv.org/abs/2506.17571

Exploring the neutron-star matter properties via the deformed nuclear reactions
Within the framework of Lanzhou quantum molecular dynamics transport model, the correlation of initial deformation and isospin diffusion is systematically investigated in collisions of $^{238}$U + $^{238}$U. The impacts of the collision centrality, symmetry energy and initial configuration on the collective flows, neutron/proton and $π^{-}/π^{+}$ ratios have been systematically investigated. It is found that the broader neutron-rich region is formed in the body-body collisions in comparison w…

Lunar and Terrestrial Time Transformation Based on the Principle of General Relativity
Min Liu, Jing-Song Ping, Wen-Xiao Li, Zhou-Jian Cao, Jie Yang, Yong-Jun Wang, Hong-Bo Jin, Wen-Zhao Zhang, Ming-Xue Shao, Jian-Guo Yan, He-Zhen Yu
https://arxiv.org/abs/2507.15456

Lunar and Terrestrial Time Transformation Based on the Principle of General Relativity
Lunar time metrology necessitates a unified temporal framework beyond Earth, requiring an independent lunar system for timekeeping, dissemination, and calendrics. Recent American publications define Lunar Coordinate Time (LTC) within relativity and propose a Terrestrial Time (TT) to LTC conversion formula. However, this formula's derivation and assumptions are contested. The complex dynamics within the solar system can be simplified by decomposing relationships into hierarchical wide-area (exte…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/11]:
- Bohdi: Heterogeneous LLM Fusion with Automatic Data Exploration
Junqi Gao, Zhichang Guo, Dazhi Zhang, Dong Li, Runze Liu, Pengfei Li, Kai Tian, Biqing Qi

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[1/5]:
- Vision-based Conflict Detection within Crowds based on High-Resolution Human Pose Estimation for ...
Kheta, Delgove, Liu, Aderogba, Pokam, Unal, Xing, Guo

Higher-Dimensional Moving Averages and Submanifold Genericity
Jiajun Cheng, Reynold Fregoli, Beinuo Guo
https://arxiv.org/abs/2507.15498 https://

Higher-Dimensional Moving Averages and Submanifold Genericity
We generalize results of Bellow, Jones, and Rosenblatt on moving ergodic averages to measure-preserving actions of $\mathbb Z^d$ and $\mathbb R^d$ for $d\geq 1$. In particular, we give necessary and sufficient conditions for the pointwise convergence of certain sequences of functions defined by averaging over families of boxes in $\mathbb Z^d$ and $\mathbb R^d$. As an application of our characterization, we show that averages along dilates of "locally flat" submanifolds in $\mathbb R^d$ do not …

Anomalous charge density wave in two-dimensional altermagnet WO
Zi-Hao Ding, Zhen-Feng Ouyang, Ze-Feng Gao, Wei Ji, Kai Liu, Peng-Jie Guo, Zhong-Yi Lu
https://arxiv.org/abs/2507.15429

Anomalous charge density wave in two-dimensional altermagnet WO
Recently, the study of novel physical properties arising from the combination of altermagnetism and other matter phases has attracted widespread attention, such as the integration of altermagnetism and topology. However, research on the combination of altermagnetism and charge density waves remains relatively sparse. In this letter, based on symmetry analysis and first-principles calculations, we demonstrate for the first time that altermagnetism and charge density waves can coexist in a two-di…

MinD: Unified Visual Imagination and Control via Hierarchical World Models
Xiaowei Chi, Kuangzhi Ge, Jiaming Liu, Siyuan Zhou, Peidong Jia, Zichen He, Yuzhen Liu, Tingguang Li, Lei Han, Sirui Han, Shanghang Zhang, Yike Guo
https://arxiv.org/abs/2506.18897

MinD: Unified Visual Imagination and Control via Hierarchical World Models
Video generation models (VGMs) offer a promising pathway for unified world modeling in robotics by integrating simulation, prediction, and manipulation. However, their practical application remains limited due to (1) slowgeneration speed, which limits real-time interaction, and (2) poor consistency between imagined videos and executable actions. To address these challenges, we propose Manipulate in Dream (MinD), a hierarchical diffusion-based world model framework that employs a dual-system des…

A B-Spline Finite Element Method for Cloth Simulation
Yuqi Meng, Yihao Shi, Kemeng Huang, Ning Guo, Taku Komura, Yin Yang, Minchen Li
https://arxiv.org/abs/2506.18867

A B-Spline Finite Element Method for Cloth Simulation
We present a B-spline finite element method (FEM) for cloth simulation. Building on quadratic B-spline basis functions, our method provides a globally $C^1$-continuous displacement field, enabling consistent and accurate discretization of both membrane and bending energies. This smooth representation effectively mitigates locking artifacts and mesh dependency issues commonly observed with linear FEM. To further improve efficiency, we develop a reduced integration scheme that separately optimize…

Investigations of the kinetic ion-acoustic soliton by the Bernstein-Greene-Kruskal integral method
Ran Guo
https://arxiv.org/abs/2507.15207 https://…

Investigations of the kinetic ion-acoustic soliton by the Bernstein-Greene-Kruskal integral method
The solitary waves are investigated through the Bernstein-Greene-Kruskal integral method with the ion response. We consider two specific cases of ions, i.e., the single stream with the waterbag distribution and the two counter-propagating streams with the Maxwellian distribution. The trapped electron distributions are derived for both two cases. The results show that the trapped electron distribution can be either a hole or a hump in the phase space, depending on the competition between the con…

EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems
Xinmeng Hou, Zhouquan Lu, Wenli Chen, Hai Hu, Qing Guo
https://arxiv.org/abs/2507.15015

EduThink4AI: Translating Educational Critical Thinking into Multi-Agent LLM Systems
Large language models (LLMs) have demonstrated significant potential as educational tutoring agents, capable of tailoring hints, orchestrating lessons, and grading with near-human finesse across various academic domains. However, current LLM-based educational systems exhibit critical limitations in promoting genuine critical thinking, failing on over one-third of multi-hop questions with counterfactual premises, and remaining vulnerable to adversarial prompts that trigger biased or factually in…

Layer-selective Cooper pairing in an alternately stacked transition metal dichalcogenide
Haojie Guo, Sandra Sajan, Iri\'an S\'anchez-Ram\'irez, Tarushi Agarwal, Alejandro Blanco Peces, Chandan Patra, Maia G. Vergniory, Rafael M. Fernandes, Ravi Prakash Singh, Fernando de Juan, Maria N. Gastiasoro, Miguel M. Ugeda
https://

Layer-selective Cooper pairing in an alternately stacked transition metal dichalcogenide
Multigap superconductivity emerges when superconducting gaps form on distinct Fermi surfaces. Arising from locally overlapping atomic orbitals, multiple superconducting bands introduce a new internal degree of freedom in the material that, however, escapes external control due to their coexistence in real space in the known multigap superconductors. Here, we show that the layered superconductor 4Hb-TaSSe - composed of alternating trigonal (H) and octahedral (T) polymorph layers - is a multigap …

Polynomial Szemer\'edi for sets with large Hausdorff dimension on the Torus
Guo-Dong Hong
https://arxiv.org/abs/2507.14407 https://

Polynomial Szemerédi for sets with large Hausdorff dimension on the Torus
Let $\mathbb{P}= \{P_1, \cdots, P_{k}\in \mathbb{R}[y]\}$ be a collection of polynomials with distinct degrees and zero constant terms. We proved that there exists $ε=ε(\mathbb{P})>0$ such that, for any compact set $E \subset \mathbb{T}$ with dim(E)$>1-ε$, we can find $y\neq 0$ so that $\{x,x+P_1(y), \cdots,x+P_k(y)\} \subset E$. The proof relies on a suitable version of the Sobolev smoothing inequality with ideas adapted from Peluse \cite{P19}, Durcik and Roos \cite{DR24}, and Krause, Mirek…

De novo design of alpha-helical peptide amphiphiles repairing fragmented collagen type I via supramolecular co-assembly
Shanshan Su, Jie Yang, Guo Zhang, Zhiquan Yu, Yuxuan Chen, Alexander van Teijlingen, Dawen Yu, Tong Li, Yubin Ke, Hua Yang, Haoran Zhang, Jialong Chen, Jiaming Sun, Yuanhao Wu
https://arxiv.org/abs/2507.14577…

De novo design of alpha-helical peptide amphiphiles repairing fragmented collagen type I via supramolecular co-assembly
The hierarchical triple-helix structure of collagen type I, Col I, is essential for extracellular matrix support and integrity. However, current reconstruction strategies face challenges such as chain mismatch, preventing proper fibril formation. Here, we report a supramolecular co-assembly strategy using a de novo-designed alpha-helical peptide amphiphile (APA) of just seven amino acids. The APA features a hydrophobic palmitic acid tail, which stabilizes the helical structure and promotes co-a…

Approximate Revenue Maximization for Diffusion Auctions
Yifan Huang, Dong Hao, Zhiyi Fan, Yuhang Guo, Bin Li
https://arxiv.org/abs/2507.14470 https://

Approximate Revenue Maximization for Diffusion Auctions
Reserve prices are widely used in practice. The problem of designing revenue-optimal auctions based on reserve price has drawn much attention in the auction design community. Although they have been extensively studied, most developments rely on the significant assumption that the target audience of the sale is directly reachable by the auctioneer, while a large portion of bidders in the economic network unaware of the sale are omitted. This work follows the diffusion auction design, which aims…

Replaced article(s) found for eess.IV. https://arxiv.org/list/eess.IV/new
[1/1]:
- Now and Future of Artificial Intelligence-based Signet Ring Cell Diagnosis: A Survey
Zhu Meng, Junhao Dong, Limei Guo, Fei Su, Jiaxuan Liu, Guangxi Wang, Zhicheng Zhao

Search for Light Dark Matter with 259-day data in PandaX-4T
Minzhen Zhang, Zihao Bo, Wei Chen, Xun Chen, Yunhua Chen, Chen Cheng, Xiangyi Cui, Manna Deng, Yingjie Fan, Deqing Fang, Xuanye Fu, Zhixing Gao, Yujie Ge, Lisheng Geng, Karl Giboni, Xunan Guo, Xuyuan Guo, Zichao Guo, Chencheng Han, Ke Han, Changda He, Jinrong He, Houqi Huang, Junting Huang, Yule Huang, Ruquan Hou, Xiangdong Ji, Yonglin Ju, Xiaorun Lan, Chenxiang Li, Jiafu Li, Mingchuan Li, Peiyuan Li, Shuaijie Li, Tao Li, Yang…

Search for Light Dark Matter with 259-day data in PandaX-4T
We present a search for light dark matter particles through their interactions with atomic electrons and nucleons, utilizing PandaX-4T data with an effective exposure of 1.04 tonne$\cdot$year for ionization-only data and 1.20 tonne$\cdot$year for paired data. Our analysis focuses on the energy range (efficiency$>$0.01) of approximately 0.33 to 3 keV for nuclear recoils, and from 0.04 to 0.39 keV for electronic recoils. We establish the most stringent constraints on spin-independent dark matter-…

Co-evolution of cosmic ray energy spectra, composition, and anisotropies
Bing-Qiang Qiao, Qiang Yuan, Yi-Qing Guo
https://arxiv.org/abs/2506.18118 https://…

Co-evolution of cosmic ray energy spectra, composition, and anisotropies
The origin of cosmic rays remains an unresolved fundamental problem in astrophysics. The synergy of multiple observational probes, including the energy spectra, the mass composition, and anisotropy is a viable way to jointly uncover this mystery. In this work, we propose that the energy-dependent of those observables in a wide energy range, from $O(10)$ GeV to ultrahigh energies of $10^{11}$ GeV, share quite a few correlated features, indicating a strong co-evolution which could be a consequenc…

Identifiability Analysis of a Pseudo-Two-Dimensional Model & Single Particle Model-Aided Parameter Estimation
L. D. Couto, K. Haghverdi, F. Guo, K. Trad, G. Mulder
https://arxiv.org/abs/2507.13931

Identifiability Analysis of a Pseudo-Two-Dimensional Model & Single Particle Model-Aided Parameter Estimation
This contribution presents a parameter identification methodology for the accurate and fast estimation of model parameters in a pseudo-two-dimensional (P2D) battery model. The methodology consists of three key elements. First, the data for identification is inspected and specific features herein that need to be captured are included in the model. Second, the P2D model is analyzed to assess the identifiability of the physical model parameters and propose alternative parameterizations that allevi…

RIDAS: A Multi-Agent Framework for AI-RAN with Representation- and Intention-Driven Agents
Kuiyuan Ding, Caili Guo, Yang Yang, Jianzhang Guo
https://arxiv.org/abs/2507.13140

RIDAS: A Multi-Agent Framework for AI-RAN with Representation- and Intention-Driven Agents
Sixth generation (6G) networks demand tight integration of artificial intelligence (AI) into radio access networks (RANs) to meet stringent quality of service (QoS) and resource efficiency requirements. Existing solutions struggle to bridge the gap between high level user intents and the low level, parameterized configurations required for optimal performance. To address this challenge, we propose RIDAS, a multi agent framework composed of representation driven agents (RDAs) and an intention dr…

Replaced article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[2/2]:
- zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning
Zhipeng Wang, Nanqing Dong, Jiahao Sun, William Knottenbelt, Yike Guo

Stabilization of jump-diffusion stochastic differential equations by hysteresis switching
Weichao Liang, Gaoyue Guo
https://arxiv.org/abs/2507.15191 https:…

Stabilization of jump-diffusion stochastic differential equations by hysteresis switching
We address the stabilization of both classical and quantum systems modeled by jump-diffusion stochastic differential equations using a novel hysteresis switching strategy. Unlike traditional methods that depend on global Lyapunov functions or require each subsystem to stabilize the target state individually, our approach employs local Lyapunov-like conditions and state-dependent switching to achieve global asymptotic or exponential stability with finitely many switches almost surely. We rigorou…

Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations
Yichen Han, Xiaoyang Hao, Keming Chen, Weibo Xiong, Jun He, Ruonan Zhang, Junjie Cao, Yue Liu, Bowen Li, Dongrui Zhang, Hui Xia, Huilei Fu, Kai Jia, Kaixuan Guo, Mingli Jin, Qingyun Meng, Ruidong Ma, Ruiqian Fang, Shaotong Guo, Xuhui Li, Yang Xiang, Ying Zhang, Yulong Liu, Yunfeng Li, Yuyi Zhang, Yuze Zhou, Zhen Wang, Zhaowen Chen

Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations
Text-to-speech (TTS) synthesis has seen renewed progress under the discrete modeling paradigm. Existing autoregressive approaches often rely on single-codebook representations, which suffer from significant information loss. Even with post-hoc refinement techniques such as flow matching, these methods fail to recover fine-grained details (e.g., prosodic nuances, speaker-specific timbres), especially in challenging scenarios like singing voice or music synthesis. We propose QTTS, a novel TTS fra…

Auto-Regressive Surface Cutting
Yang Li, Victor Cheung, Xinhai Liu, Yuguang Chen, Zhongjin Luo, Biwen Lei, Haohan Weng, Zibo Zhao, Jingwei Huang, Zhuo Chen, Chunchao Guo
https://arxiv.org/abs/2506.18017

Auto-Regressive Surface Cutting
Surface cutting is a fundamental task in computer graphics, with applications in UV parameterization, texture mapping, and mesh decomposition. However, existing methods often produce technically valid but overly fragmented atlases that lack semantic coherence. We introduce SeamGPT, an auto-regressive model that generates cutting seams by mimicking professional workflows. Our key technical innovation lies in formulating surface cutting as a next token prediction task: sample point clouds on mesh…

Factorization and Resummation for the Nearside Energy-Energy Correlators
Yuxun Guo, Feng Yuan, Wenbin Zhao
https://arxiv.org/abs/2507.15820 https://…

Factorization and Resummation for the Nearside Energy-Energy Correlators
By utilizing the di-hadron fragmentation formalism, we extend the previous factorization of nearside energy-energy correlators (EEC) in the collinear limit and derive an all order resummation in the Fourier transform $b_T$-space. A perfect matching is obtained when we compare to the fixed-order results. We further demonstrate the resummation effects for the EEC in $e^+e^-$ annihilation and show that they will significantly improve the theoretical predictions at small angles.

Binary Neutron Star Mergers as Potential Sources for Ultra-High-Energy Cosmic Rays and High-Energy Neutrinos
Gang Guo, Yong-Zhong Qian, Meng-Ru Wu
https://arxiv.org/abs/2506.17581

Binary Neutron Star Mergers as Potential Sources for Ultra-High-Energy Cosmic Rays and High-Energy Neutrinos
Recent studies suggest that the most energetic cosmic rays, exceeding 100 EeV, may primarily consist of $r$-process nuclei. This highlights binary neutron star mergers and collapsars as promising sources of ultra-high-energy cosmic rays (UHECRs). Building on these insights, we examine the conditions that facilitate the efficient production of UHE $r$-process nuclei during the prompt radiation (PR), extended emission (EE), and plateau emission phases of short gamma-ray bursts (sGRBs) following n…

BugScope: Learn to Find Bugs Like Human
Jinyao Guo, Chengpeng Wang, Dominic Deluca, Jinjie Liu, Zhuo Zhang, Xiangyu Zhang
https://arxiv.org/abs/2507.15671 …

BugScope: Learn to Find Bugs Like Human
Detecting software bugs remains a fundamental challenge due to the extensive diversity of real-world defects. Traditional static analysis tools often rely on symbolic workflows, which restrict their coverage and hinder adaptability to customized bugs with diverse anti-patterns. While recent advances incorporate large language models (LLMs) to enhance bug detection, these methods continue to struggle with sophisticated bugs and typically operate within limited analysis contexts. To address these…

Music-Aligned Holistic 3D Dance Generation via Hierarchical Motion Modeling
Xiaojie Li, Ronghui Li, Shukai Fang, Shuzhao Xie, Xiaoyang Guo, Jiaqing Zhou, Junkun Peng, Zhi Wang
https://arxiv.org/abs/2507.14915

Music-Aligned Holistic 3D Dance Generation via Hierarchical Motion Modeling
Well-coordinated, music-aligned holistic dance enhances emotional expressiveness and audience engagement. However, generating such dances remains challenging due to the scarcity of holistic 3D dance datasets, the difficulty of achieving cross-modal alignment between music and dance, and the complexity of modeling interdependent motion across the body, hands, and face. To address these challenges, we introduce SoulDance, a high-precision music-dance paired dataset captured via professional motio…

Strategy Evolution in the Adoption of Conservation Tillage Technology under Time Preference Heterogeneity and Lemon Market: Insights from Evolutionary Dynamics
Dingyi Wang, Ruqiang Guo, Qian Lu
https://arxiv.org/abs/2507.15497

Strategy Evolution in the Adoption of Conservation Tillage Technology under Time Preference Heterogeneity and Lemon Market: Insights from Evolutionary Dynamics
The promotion of Conservation Tillage Technology (CTT) is critical for mitigating global soil degradation, yet their actual adoption rates remain substantially lower than anticipated targets. Existing research predominantly focuses on static factor analyses, failing to adequately capture the dynamic evolutionary mechanisms of farmer strategic interactions and the impacts of information asymmetries in agricultural markets. This study constructs an evolutionary game model integrating heterogeneou…

DuetGen: Music Driven Two-Person Dance Generation via Hierarchical Masked Modeling
Anindita Ghosh, Bing Zhou, Rishabh Dabral, Jian Wang, Vladislav Golyanik, Christian Theobalt, Philipp Slusallek, Chuan Guo
https://arxiv.org/abs/2506.18680

DuetGen: Music Driven Two-Person Dance Generation via Hierarchical Masked Modeling
We present DuetGen, a novel framework for generating interactive two-person dances from music. The key challenge of this task lies in the inherent complexities of two-person dance interactions, where the partners need to synchronize both with each other and with the music. Inspired by the recent advances in motion synthesis, we propose a two-stage solution: encoding two-person motions into discrete tokens and then generating these tokens from music. To effectively capture intricate interactions…

Exploring the Frontiers of Cosmic Ray Physics: Perspectives on GRANDProto300 and the GRAND Project
Kewen Zhang, Yi Zhang, Yi-Qing Guo
https://arxiv.org/abs/2506.16274

Exploring the Frontiers of Cosmic Ray Physics: Perspectives on GRANDProto300 and the GRAND Project
The Giant Radio Array for Neutrino Detection (GRAND) is an envisioned large-scale radio array designed to detect ultra-high-energy cosmic rays (UHECRs, $E > 100$ PeV) and neutrinos. Employing cost-effective antennas distributed across vast areas, GRAND is optimized to observe the rare flux of ultra-high-energy particles with high precision. The GRANDProto300 (GP300) pathfinder array, currently under deployment, targets the $10^{16.5} - 10^{18}$ eV range and is anticipated to achieve approximate…

GAP-LA: GPU-Accelerated Performance-Driven Layer Assignment
Chunyuan Zhao, Zizheng Guo, Zuodong Zhang, Yibo Lin
https://arxiv.org/abs/2507.13375 https://…

GAP-LA: GPU-Accelerated Performance-Driven Layer Assignment
Layer assignment is critical for global routing of VLSI circuits. It converts 2D routing paths into 3D routing solutions by determining the proper metal layer for each routing segments to minimize congestion and via count. As different layers have different unit resistance and capacitance, layer assignment also has significant impacts to timing and power. With growing design complexity, it becomes increasingly challenging to simultaneously optimize timing, power, and congestion efficiently. Exi…

VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Haichao Liu, Haoren Guo, Pei Liu, Benshan Ma, Yuxiang Zhang, Jun Ma, Tong Heng Lee
https://arxiv.org/abs/2507.15266

VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Scene understanding and risk-aware attentions are crucial for human drivers to make safe and effective driving decisions. To imitate this cognitive ability in urban autonomous driving while ensuring the transparency and interpretability, we propose a vision-language model (VLM)-enhanced unified decision-making and motion control framework, named VLM-UDMC. This framework incorporates scene reasoning and risk-aware insights into an upper-level slow system, which dynamically reconfigures the optim…

Precise Measurement of $^{216}$Po Half-life with Exact Parent-daughter Pairing in PandaX-4T
PandaX Collaboration, Chenxiang Li, Zihao Bo, Wei Chen, Xun Chen, Yunhua Chen, Chen Cheng, Xiangyi Cui, Manna Deng, Yingjie Fan, Deqing Fang, Xuanye Fu, Zhixing Gao, Yujie Ge, Lisheng Geng, Karl Giboni, Xunan Guo, Xuyuan Guo, Zichao Guo, Chencheng Han, Ke Han, Changda He, Jinrong He, Houqi Huang, Junting Huang, Yule Huang, Ruquan Hou, Xiangdong Ji, Yonglin Ju, Xiaorun Lan, Jiafu Li, Mingchuan Li…

Precise Measurement of $^{216}$Po Half-life with Exact Parent-daughter Pairing in PandaX-4T
We report a precise measurement of $^{216}\rm Po$ half-life using the PandaX-4T liquid xenon time projection chamber (TPC). $^{220}\rm Rn $, emanating from a $^{228}\rm Th $ calibration source, is injected to the detector and undergoes successive $α$ decays, first to $^{216}\rm Po$ and then to $^{212}\rm Pb$. PandaX-4T detector measures the 5-dimensional (5D) information of each decay, including time, energy, and 3-dimensional positions. Therefore, we can identify the $^{220}\rm Rn $ and $^{21…

H-NeiFi: Non-Invasive and Consensus-Efficient Multi-Agent Opinion Guidance
Shijun Guo, Haoran Xu, Yaming Yang, Ziyu Guan, Wei Zhao, Xinyi Zhang, Yishan Song, Jiwei Chen
https://arxiv.org/abs/2507.13370

H-NeiFi: Non-Invasive and Consensus-Efficient Multi-Agent Opinion Guidance
The openness of social media enables the free exchange of opinions, but it also presents challenges in guiding opinion evolution towards global consensus. Existing methods often directly modify user views or enforce cross-group connections. These intrusive interventions undermine user autonomy, provoke psychological resistance, and reduce the efficiency of global consensus. Additionally, due to the lack of a long-term perspective, promoting local consensus often exacerbates divisions at the mac…

Testing the cosmic distance duality relation with baryon acoustic oscillations and supernovae data
Tian-Nuo Li, Guo-Hong Du, Peng-Ju Wu, Jing-Zhao Qi, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2507.13811

Testing the cosmic distance duality relation with baryon acoustic oscillations and supernovae data
One of the most fundamental relationships in modern cosmology is the cosmic distance duality relation (CDDR), which describes the relationship between the angular diameter distance ($D_{\rm A}$) and the luminosity distance ($D_{\rm L}$), and is expressed as: $η(z)=D_{\rm L}(z)(1+z)^{-2}/D_{\rm A}(z)=1$. In this work, we conduct a comprehensive test of the CDDR by combining baryon acoustic oscillation (BAO) data from the SDSS and DESI surveys with type Ia supernova (SN) data from PantheonPlus a…

Time-Frequency Transfer over Optical Fiber
Ziyang Chen, Yufei Zhang, Bin Luo, Hong Guo
https://arxiv.org/abs/2507.13745 https://arxiv…

Time-Frequency Transfer over Optical Fiber
Optical time-frequency transfer establishes the metrological linkage in large-scale clock networks, which facilitates various applications. Fiber-based transfer benefits from the abundant deployment of fiber infrastructures to achieve this advantage. In this Review, we provide an overview of the advances in optical two-way time-frequency transfer, which began with characterizing the time-frequency transfer stability. Then, we discuss the system configuration, key modules, main challenges, and m…

Temperature dependent single- and double-quantum relaxation of negatively charged boron vacancies in hexagonal boron nitride
Lin-Ke Xie, Wei Liu, Kaiyu Huang, Nai-Jie Guo, Jun-You Liu, Yu-Hang Ma, Ya-Qi Wu, Yi-Tao Wang, Zhao-an Wang, Xiao-Dong Zeng, Jia-Ming Ren, Chun Ao, Shuo Deng, Haifei Lu, Jian-Shun Tang, Chuan-Feng Li, Guang-Can Guo
https://

Temperature dependent single- and double-quantum relaxation of negatively charged boron vacancies in hexagonal boron nitride
The negatively charged boron vacancy in two-dimensional hexagonal boron nitride has emerged as a promising candidate for quantum sensing. The coherence time of this defect spins which coherent quantum sensing resides in is limited spin-phonon interactions, while the underlying physical mechanism of the corresponding high-temperature behavior is still not fully understood. Here, we probe the single- and double-quantum relaxation rates on this center over the temperature range from 293 to 393 K. …

Strongly correlated altermagnet CaCrO$_3$
Zhenfeng Ouyang, Peng-Jie Guo, Rong-Qiang He, Zhong-Yi Lu
https://arxiv.org/abs/2507.14081 https://

Strongly correlated altermagnet CaCrO$_3$
Altermagnetism, a newly discovered magnetic phase, has spurred growing research activity. Studies from a perspective of dynamical electronic correlation still remain scarce. Employing density functional theory plus dynamical mean-field theory (DFT+DMFT) that incorporates dynamical electronic correlation, we demonstrate that CaCrO$_3$ is a strongly correlated altermagnet. Our DFT+DMFT calculations successfully reproduce the correlated metallic behavior of CaCrO$_3$ and quantitatively capture the…

ISAC: From Human to Environmental Sensing
Kai Wu, Zhongqin Wang, Shu-Lin Chen, J. Andrew Zhang, Y. Jay Guo
https://arxiv.org/abs/2507.13766 https://…

ISAC: From Human to Environmental Sensing
Integrated Sensing and Communications (ISAC) is poised to become one of the defining capabilities of the sixth generation (6G) wireless communications systems, enabling the network infrastructure to jointly support high-throughput communications and situational awareness. While recent advances have explored ISAC for both human-centric applications and environmental monitoring, existing research remains fragmented across these domains. This paper provides the first unified review of ISAC-enabled…

Feature Complementation Architecture for Visual Place Recognition
Weiwei Wang, Meijia Wang, Haoyi Wang, Wenqiang Guo, Jiapan Guo, Changming Sun, Lingkun Ma, Weichuan Zhang
https://arxiv.org/abs/2506.12401

Feature Complementation Architecture for Visual Place Recognition
Visual place recognition (VPR) plays a crucial role in robotic localization and navigation. The key challenge lies in constructing feature representations that are robust to environmental changes. Existing methods typically adopt convolutional neural networks (CNNs) or vision Transformers (ViTs) as feature extractors. However, these architectures excel in different aspects -- CNNs are effective at capturing local details. At the same time, ViTs are better suited for modeling global context, mak…

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Baoshen Guo, Zhiqing Hong, Junyi Li, Shenhao Wang, Jinhua Zhao
https://arxiv.org/abs/2507.13366

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Urban mobility data has significant connections with economic growth and plays an essential role in various smart-city applications. However, due to privacy concerns and substantial data collection costs, fine-grained human mobility trajectories are difficult to become publicly available on a large scale. A promising solution to address this issue is trajectory synthesizing. However, existing works often ignore the inherent structural complexity of trajectories, unable to handle complicated hig…

Replaced article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[2/2]:
- Tensor network algorithm to solve polaron impurity problems
Ruofan Chen, Lei Gu, Chu Guo

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation
Changxin Ke, Rui Zhang, Shuo Wang, Li Ding, Guangli Li, Yuanbo Wen, Shuoming Zhang, Ruiyuan Xu, Jin Qin, Jiaming Guo, Chenxi Wang, Ling Li, Qi Guo, Yunji Chen
https://arxiv.org/abs/2506.11153

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation
The rise of GPU-based high-performance computing (HPC) has driven the widespread adoption of parallel programming models such as CUDA. Yet, the inherent complexity of parallel programming creates a demand for the automated sequential-to-parallel approaches. However, data scarcity poses a significant challenge for machine learning-based sequential-to-parallel code translation. Although recent back-translation methods show promise, they still fail to ensure functional equivalence in the translate…

Generation of Near-ideal Indistinguishable Two-Photon State by Incoherent Light
Yue-Wei Song, Ming-Yuan Gao, Zhi-Cheng Guo, Zheng-He Zhou, Yin-Hai Li, Guang-Can Guo, Zhi-Yuan Zhou, Bao-Sen Shi
https://arxiv.org/abs/2507.12066

Generation of Near-ideal Indistinguishable Two-Photon State by Incoherent Light
High-quality quantum states lie at the heart of advanced quantum information processing. The degree of photon indistinguishability is critical for applications from photonic quantum computation to precision metrology. The two-photon Hong-Ou-Mandel (HOM) interference effect provides a rigorous quantification method, with its visibility serving as the ultimate benchmark for source quality. Generally, the coherent pumping is widely regarded as indispensable for the preparation of quantum sources. …

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/7]:
- A Comprehensive Survey on Continual Learning in Generative Models
Guo, Zeng, Zhu, Wang, Wang, Zhou, Zhao, Liu, Ma, Wang, Zhang, Liu

Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Shuo Xing, Lanqing Guo, Hongyuan Hua, Seoyoung Lee, Peiran Li, Yufei Wang, Zhangyang Wang, Zhengzhong Tu
https://arxiv.org/abs/2506.15645

Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Recent Multimodal Large Language Models (MLLMs) excel on benchmark vision-language tasks, yet little is known about how input visual quality shapes their responses. Does higher perceptual quality of images already translate to better MLLM understanding? We conduct the first systematic study spanning leading MLLMs and a suite of vision-language benchmarks, applying controlled degradations and stylistic shifts to each image. Surprisingly, we uncover a visual-quality paradox: model, task, and even…

The Double-Episode Jet Genesis of the eROSITA and Fermi Bubbles
Ruiyu Zhang, Fulai Guo, Shaokun Xie, Ruofei Zhang, Shumin Wang, Guobin Mou
https://arxiv.org/abs/2507.13665

The Double-Episode Jet Genesis of the eROSITA and Fermi Bubbles
The Fermi and eROSITA bubbles are two pairs of large diffuse multi-band structures detected in our Milky Way galaxy, yet their origins remain uncertain. Using three-dimensional hydrodynamic simulations, we investigate the model where these bubbles were produced by two successive active galactic nucleus jet activities from the Galactic center, with their edges delineated by the correspondingly driven forward shocks. Our simulations successfully reproduce the observed morphology, multi-band X-ray…

High-Efficiency Quantum Memory of Full-Bandwidth Squeezed Light
Jinxian Guo, Meihong Wang, Zeliang Wu, Chenyu Qiao, Fengyi Xu, Xiaoran Zhang, Xiaolong Su, Liqing Chen, Weiping Zhang
https://arxiv.org/abs/2506.15399

High-Efficiency Quantum Memory of Full-Bandwidth Squeezed Light
In continuous-variable quantum information processing, it is crucial to develop high-efficiency and broadband quantum memory of squeezed light, which enables the storage of full-bandwidth information. Here, we present a quantum memory of squeezed light with up to 24 MHz bandwidth, which is at least 12 times that of previous narrowband resonant memory systems, via a far-off resonant Raman process. We achieve output squeezing of as high as 1.0 dB with fidelity above 92% and a memory efficiency of…

VideoITG: Multimodal Video Understanding with Instructed Temporal Grounding
Shihao Wang, Guo Chen, De-an Huang, Zhiqi Li, Minghan Li, Guilin Li, Jose M. Alvarez, Lei Zhang, Zhiding Yu
https://arxiv.org/abs/2507.13353

VideoITG: Multimodal Video Understanding with Instructed Temporal Grounding
Recent studies have revealed that selecting informative and relevant video frames can significantly improve the performance of Video Large Language Models (Video-LLMs). Current methods, such as reducing inter-frame redundancy, employing separate models for image-text relevance assessment, or utilizing temporal video grounding for event localization, substantially adopt unsupervised learning paradigms, whereas they struggle to address the complex scenarios in long video understanding. We propose…