Tootfinder

What is Exciting About Raiders Safety Isaiah Pola-Mao? https://www.si.com/nfl/raiders/patrick-graham-las-vegas-isaiah-pola-mao-

What is Exciting About Raiders Safety Isaiah Pola-Mao? https://www.si.com/nfl/raiders/patrick-graham-las-vegas-isaiah-pola-mao-

Clip Your Sequences Fairly: Enforcing Length Fairness for Sequence-Level RL
Hanyi Mao, Quanjia Xiao, Lei Pang, Haixiao Liu
https://arxiv.org/abs/2509.09177 https://

Clip Your Sequences Fairly: Enforcing Length Fairness for Sequence-Level RL
We propose FSPO (Fair Sequence Policy Optimization), a sequence-level reinforcement learning method for LLMs that enforces length-fair clipping directly in the importance-sampling (IS) weight space. We revisit sequence-level RL methods and identify a mismatch when PPO/GRPO-style clipping is transplanted to sequences: a fixed clip range systematically reweights short vs. long responses, distorting the effective objective. Theoretically, we formalize length fairness via a Length Reweighting Error…

Region-Wise Correspondence Prediction between Manga Line Art Images
Yingxuan Li, Jiafeng Mao, Qianru Qiu, Yusuke Matsui
https://arxiv.org/abs/2509.09501 https://

Region-Wise Correspondence Prediction between Manga Line Art Images
Understanding region-wise correspondence between manga line art images is a fundamental task in manga processing, enabling downstream applications such as automatic line art colorization and in-between frame generation. However, this task remains largely unexplored, especially in realistic scenarios without pre-existing segmentation or annotations. In this paper, we introduce a novel and practical task: predicting region-wise correspondence between raw manga line art images without any pre-exis…

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
Jason Chou, Ao Liu, Yuchi Deng, Zhiying Zeng, Tao Zhang, Haotian Zhu, Jianwei Cai, Yue Mao, Chenchen Zhang, Lingyun Tan, Ziyan Xu, Bohui Zhai, Hengyi Liu, Speed Zhu, Wiggin Zhou, Fengzong Lian
https://arxiv.org/abs/2508.09101

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains, with code generation emerging as a key area of focus. While numerous benchmarks have been proposed to evaluate their code generation abilities, these benchmarks face several critical limitations. First, they often rely on manual annotations, which are time-consuming and difficult to scale across different programming languages and problem complexities. Second, most existing benchmarks focus primarily …

Kinetostatics and Particle-Swarm Optimization of Vehicle-Mounted Underactuated Metamorphic Loading Manipulators
Nan Mao, Guanglu Jia, Junpeng Chen, Emmanouil Spyrakos-Papastavridis, Jian S. Dai
https://arxiv.org/abs/2509.09093

Kinetostatics and Particle-Swarm Optimization of Vehicle-Mounted Underactuated Metamorphic Loading Manipulators
Fixed degree-of-freedom (DoF) loading mechanisms often suffer from excessive actuators, complex control, and limited adaptability to dynamic tasks. This study proposes an innovative mechanism of underactuated metamorphic loading manipulators (UMLM), integrating a metamorphic arm with a passively adaptive gripper. The metamorphic arm exploits geometric constraints, enabling the topology reconfiguration and flexible motion trajectories without additional actuators. The adaptive gripper, driven en…

GeoJSON Agents:A Multi-Agent LLM Architecture for Geospatial Analysis-Function Calling vs Code Generation
Qianqian Luo, Liuchang Xu, Qingming Lin, Sensen Wu, Ruichen Mao, Chao Wang, Hailin Feng, Bo Huang, Zhenhong Du
https://arxiv.org/abs/2509.08863

Mano a Mano con Isaiah Pola-Mao https://www.raiders.com/video/mano-a-mano-con-isaiah-pola-mao-nfl-2025

Time Ordering Effects and Destruction of Quasiparticles in Two-dimensional Holographic CFTs
Weibo Mao, Masahiro Nozaki
https://arxiv.org/abs/2508.07645 https://

Time Ordering Effects and Destruction of Quasiparticles in Two-dimensional Holographic CFTs
In this paper, we investigate the entanglement dynamics induced by a composite operator, defined as the local operator evolved with the time evolution operator constructed of the Euclidean and Lorentzian ones. The systems under consideration are described by two-dimensional holographic conformal field theories (2d holographic CFTs), the theories described by gravity. Then, we find that the time ordering of Euclidean and Lorentzian time evolutions affects the behavior of bipartite entanglement a…

Secure Transmission for Cell-Free Symbiotic Radio Communications with Movable Antenna: Continuous and Discrete Positioning Designs
Bin Lyu, Jiayu Guan, Meng Hua, Changsheng You, Tianqi Mao, Abbas Jamalipour
https://arxiv.org/abs/2508.06868

Secure Transmission for Cell-Free Symbiotic Radio Communications with Movable Antenna: Continuous and Discrete Positioning Designs
In this paper, we study a movable antenna (MA) empowered secure transmission scheme for reconfigurable intelligent surface (RIS) aided cell-free symbiotic radio (SR) system. Specifically, the MAs deployed at distributed access points (APs) work collaboratively with the RIS to establish high-quality propagation links for both primary and secondary transmissions, as well as suppressing the risk of eavesdropping on confidential primary information. We consider both continuous and discrete MA posit…

Mano a Mano con Isaiah Pola-Mao https://www.raiders.com/video/mano-a-mano-con-isaiah-pola-mao-nfl-2025

AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives
Haoxiang Luo, Yu Yan, Yanhui Bian, Wenjiao Feng, Ruichen Zhang, Yinqiu Liu, Jiacheng Wang, Gang Sun, Dusit Niyato, Hongfang Yu, Abbas Jamalipour, Shiwen Mao
https://arxiv.org/abs/2509.09193

AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives
Artificial Intelligence (AI) techniques play a pivotal role in optimizing wireless communication networks. However, traditional deep learning approaches often act as closed boxes, lacking the structured reasoning abilities needed to tackle complex, multi-step decision problems. This survey provides a comprehensive review and outlook of reasoning-enabled AI in wireless communication networks, with a focus on Large Language Models (LLMs) and other advanced reasoning paradigms. In particular, LLM-…

Exploring Palette based Color Guidance in Diffusion Models
Qianru Qiu, Jiafeng Mao, Xueting Wang
https://arxiv.org/abs/2508.08754 https://arxiv.org/pdf/250…

Exploring Palette based Color Guidance in Diffusion Models
With the advent of diffusion models, Text-to-Image (T2I) generation has seen substantial advancements. Current T2I models allow users to specify object colors using linguistic color names, and some methods aim to personalize color-object association through prompt learning. However, existing models struggle to provide comprehensive control over the color schemes of an entire image, especially for background elements and less prominent objects not explicitly mentioned in prompts. This paper prop…

Learning an Implicit Physics Model for Image-based Fluid Simulation
Emily Yue-Ting Jia, Jiageng Mao, Zhiyuan Gao, Yajie Zhao, Yue Wang
https://arxiv.org/abs/2508.08254 https://

Learning an Implicit Physics Model for Image-based Fluid Simulation
Humans possess an exceptional ability to imagine 4D scenes, encompassing both motion and 3D geometry, from a single still image. This ability is rooted in our accumulated observations of similar scenes and an intuitive understanding of physics. In this paper, we aim to replicate this capacity in neural networks, specifically focusing on natural fluid imagery. Existing methods for this task typically employ simplistic 2D motion estimators to animate the image, leading to motion predictions that …

Jakobi Meyers, Dont'e Thornton Jr., Michael Mayer and Isaiah Pola-Mao Scrums | Week 2 vs. Chargers https://www.raiders.com/video/jakobi-meyers-donte-thornton-michael-mayer-isaiah-pola-mao-scrums-week-2-chargers

Realizing the Haldane Model in Thermal Atoms
Jiefei Wang, Jianhao Dai, Ruosong Mao, Yunzhou Lu, Xiao Liu, Huizhu Hu, Shi-Yao Zhu, Xingqi Xu, Han Cai, Da-Wei Wang
https://arxiv.org/abs/2509.08411

Realizing the Haldane Model in Thermal Atoms
Topological materials hold great promise for developing next-generation devices with transport properties that remain resilient in the presence of local imperfections. However, their susceptibility to thermal noise has posed a major challenge. In particular, the Haldane model, a cornerstone in topological physics, generally requires cryogenic temperatures for experimental realization, limiting both the investigation of topologically robust quantum phenomena and their practical applications. In …

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/4]:
- CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge
Qikai Wei, Mingzhi Yang, Jinqiang Wang, Wenwei Mao, Jiabo Xu, Huansheng Ning

Ultra-Efficient Reconstruction of Anisotropic Hyperuniform Continuous Random Fields in 2D and 3D via Generalized Spectral Filtering
Liyu Zhong, Sheng Mao
https://arxiv.org/abs/2509.08675

Ultra-Efficient Reconstruction of Anisotropic Hyperuniform Continuous Random Fields in 2D and 3D via Generalized Spectral Filtering
Hyperuniform continuous random fields suppress large-scale fluctuations while preserving rich local disorder, making them highly attractive for next-generation photonic, thermal and mechanical materials. However, traditional reconstruction techniques often suffer from limited spectral control or excessive computational cost, especially in high-resolution 2D and 3D settings. In this work, we present an ultra-efficient generative algorithm based on generalized superellipse spectral filtering, whi…

On the Hardness of Unsupervised Domain Adaptation: Optimal Learners and Information-Theoretic Perspective
Zhiyi Dong, Zixuan Liu, Yongyi Mao
https://arxiv.org/abs/2507.06552

On the Hardness of Unsupervised Domain Adaptation: Optimal Learners and Information-Theoretic Perspective
This paper studies the hardness of unsupervised domain adaptation (UDA) under covariate shift. We model the uncertainty that the learner faces by a distribution $π$ in the ground-truth triples $(p, q, f)$ -- which we call a UDA class -- where $(p, q)$ is the source -- target distribution pair and $f$ is the classifier. We define the performance of a learner as the overall target domain risk, averaged over the randomness of the ground-truth triple. This formulation couples the source distributi…

A Survey on Artificial Noise for Physical Layer Security: Opportunities, Technologies, Guidelines, Advances, and Trends
Hong Niu, Yue Xiao, Xia Lei, Jiangong Chen, Zhihan Xiao, Mao Li, Chau Yuen
https://arxiv.org/abs/2507.06500

A Survey on Artificial Noise for Physical Layer Security: Opportunities, Technologies, Guidelines, Advances, and Trends
Due to the broadcast nature of wireless communications, physical-layer security has attracted increasing concerns from both academia and industry. Artificial noise (AN), as one of the promising physical-layer security techniques, is capable of utilizing the spatial degree-of-freedom of channels to effectively enhance the security of wireless communications. In contrast to other physicallayer security techniques, the key distinguishing feature of AN is to generate specific interfering signals ac…

The Trump administration has accomplished something that Hitler, Stalin, Mao, and other dictators desired.
-- It destroyed the Voice of America.
Until mid-March, VOA had been on the air continuously for 83 years.
Starting in 1942 with shortwave broadcasts in German to counter Nazi propaganda,
America’s external voice had expanded to nearly 50 languages,
with a weekly combined audience of more than 350 million people worldwide, watching on TV, listening on radi…

I Fought To Keep VOA Independent. Now It’s Gone.
The Trump administration has accomplished something that Hitler, Stalin, Mao, and other dictators desired. It destroyed the Voice of America. Until mid-March, VOA had been on the air continuously for 83 years. Starting in 1942 with shortwave broadcasts in German to counter Nazi propaganda, America’s...

Validity and Power of Heavy-Tailed Combination Tests under Asymptotic Dependence
Lin Gui, Tiantian Mao, Jingshu Wang, Ruodu Wang
https://arxiv.org/abs/2508.05818 https://…

Validity and Power of Heavy-Tailed Combination Tests under Asymptotic Dependence
Heavy-tailed combination tests, such as the Cauchy combination test and harmonic mean p-value method, are widely used for testing global null hypotheses by aggregating dependent p-values. However, their theoretical guarantees under general dependence structures remain limited. We develop a unified framework using multivariate regularly varying copulas to model the joint behavior of p-values near zero. Within this framework, we show that combination tests remain asymptotically valid when the tra…

ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System
Dong Han, Zhehong Ai, Pengxiang Cai, Shuzhou Sun, Shanya Lu, Jianpeng Chen, Ben Gao, Lingli Ge, Weida Wang, Xiangxin Zhou, Xihui Liu, Mao Su, Wanli Ouyang, Lei Bai, Dongzhan Zhou, Tao XU, Yuqiang Li, Shufei Zhang
https://arxiv.org/abs/2509.08736

ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System
The efficiency of Bayesian optimization (BO) in chemistry is often hindered by sparse experimental data and complex reaction mechanisms. To overcome these limitations, we introduce ChemBOMAS, a new framework named LLM-Enhanced Multi-Agent System for accelerating BO in chemistry. ChemBOMAS's optimization process is enhanced by LLMs and synergistically employs two strategies: knowledge-driven coarse-grained optimization and data-driven fine-grained optimization. First, in the knowledge-driven coa…

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Realizing the Haldane Model in Thermal Atoms
Wang, Dai, Mao, Lu, Liu, Hu, Zhu, Xu, Cai, Wang

One Raiders Play Worth Rooting for This Season https://www.si.com/nfl/raiders/isaiah-pola-mao-las-vetas-troy-polamalu-pete-carroll

Nonabelian Kodaira-Spencer maps
Yixuan Fu, Mao Sheng
https://arxiv.org/abs/2509.06050 https://arxiv.org/pdf/2509.06050

Nonabelian Kodaira-Spencer maps
We give an explicit formula of the associated graded map to the nonabelian Gauss-Manin connection with respect to the nonabelian Hodge filtration.

OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding
JingLi Lin, Chenming Zhu, Runsen Xu, Xiaohan Mao, Xihui Liu, Tai Wang, Jiangmiao Pang
https://arxiv.org/abs/2507.07984

OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding
Recent advances in multimodal large language models (MLLMs) have shown remarkable capabilities in integrating vision and language for complex reasoning. While most existing benchmarks evaluate models under offline settings with a fixed set of pre-recorded inputs, we introduce OST-Bench, a benchmark designed to evaluate Online Spatio-Temporal understanding from the perspective of an agent actively exploring a scene. The Online aspect emphasizes the need to process and reason over incrementally a…

A large language model system for the field of chemical engineering technology
Heng Zhang, Jibin Zhou, Feiyang Xu, Jian Cui, Yi Li, Fan Yang, Hao Wang, Xin Li, Mao Ye
https://arxiv.org/abs/2509.07034

A large language model system for the field of chemical engineering technology
The development of chemical engineering technology is a multi-stage process that encompasses laboratory research, scaling up, and industrial deployment. This process demands interdisciplinary col laboration and typically incurs significant time and economic costs. To tackle these challenges, we have developed a system based on ChemELLM in this work. This system enables users to interact freely with the chem ical engineering model, establishing a new paradigm for AI-driven in novation an…

LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interaction
Weichu Liu, Jing Xiong, Yuxuan Hu, Zixuan Li, Minghuan Tan, Ningning Mao, Chenyang Zhao, Zhongwei Wan, Chaofan Tao, Wendong Xu, Hui Shen, Chengming Li, Lingpeng Kong, Ngai Wong
https://arxiv.org/abs/2509.07403…

LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interaction
Large language models (LLMs) make significant progress in Emotional Intelligence (EI) and long-context understanding. However, existing benchmarks tend to overlook certain aspects of EI in long-context scenarios, especially under realistic, practical settings where interactions are lengthy, diverse, and often noisy. To move towards such realistic settings, we present LongEmotion, a benchmark specifically designed for long-context EI tasks. It covers a diverse set of tasks, including Emotion Cla…

Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- An algorithm with a delay of $\mathcal{O}(k\Delta)$ for enumerating connected induced subgraphs o...
Chenglong Xiao, Chengyong Mao, Shanshan Wang

Replaced article(s) found for gr-qc. https://arxiv.org/list/gr-qc/new
[3/3]:
- The degeneracy between microlensing wave effect and precession in strongly lensed gravitational wave
Xikai Shan, Huan Yang, Shude Mao, Otto A. Hannuksela

Big plays on both sides of the ball secures Raiders the Week 1 win vs. Patriots https://www.raiders.com/video/brock-bowers-isaiah-pola-mao-recap-week-1-win-patriots-nfl

An Efficient Max-Min Fair Resource Optimization Algorithm for Rate-Splitting Multiple Access
Facheng Luo, Yijie Mao
https://arxiv.org/abs/2507.04201 https:…

An Efficient Max-Min Fair Resource Optimization Algorithm for Rate-Splitting Multiple Access
The max-min fairness (MMF) problem in rate-splitting multiple access (RSMA) is known to be challenging due to its non-convex and non-smooth nature, as well as the coupled beamforming and common rate variables. Conventional algorithms to address this problem often incur high computational complexity or degraded MMF rate performance. To address these challenges, in this work, we propose a novel optimization algorithm named extragradient-fractional programming (EG-FP) to address the MMF problem of…

Canonicalization of the E value from BLAST similarity search -- dissimilarity measure and distance function for a metric space of protein sequences
Boryeu Mao
https://arxiv.org/abs/2509.06849

Canonicalization of the E value from BLAST similarity search -- dissimilarity measure and distance function for a metric space of protein sequences
Sequence matching algorithms such as BLAST and FASTA have been widely used in searching for evolutionary origin and biological functions of newly discovered nucleic acid and protein sequences. As parts of these search tools, alignment scores and E values are useful indicators of the quality of search results from querying a database of annotated sequences, whereby a high alignment score (and inversely a low E value) reflects significant similarity between the query and the subject (target) sequ…

Isaiah Pola-Mao picks up on Lock's read with INT https://www.nfl.com/videos/isaiah-pola-mao-picks-up-on-lock-s-read-with-int

Integral formulas for under/overdetermined differential operators via recovery on curves and the finite-dimensional cokernel condition I: General theory
Philip Isett, Yuchen Mao, Sung-Jin Oh, Zhongkai Tao
https://arxiv.org/abs/2509.04617

Integral formulas for under/overdetermined differential operators via recovery on curves and the finite-dimensional cokernel condition I: General theory
We introduce a new versatile method for constructing solution operators (i.e., right-inverses up to a finite rank operator) for a wide class of underdetermined PDEs $P u = f$, which are regularizing of optimal order and, more interestingly, whose integral kernels have certain prescribed support properties. By duality, we simultaneously obtain integral representation formulas (i.e., left-inverses up to a finite rank operator) for overdetermined PDEs $P^{\ast} v = g$ with analogous properties, wh…

First Constraint on P-odd/T-odd Cross Section in Polarized Neutron Transmission through Transversely Polarized $^{139}$La
Rintaro Nakabe, Clayton J. Auton, Shunsuke Endo, Hiroyuki Fujioka, Vladimir Gudkov, Katsuya Hirota, Ikuo Ide, Takashi Ino, Motoyuki Ishikado, Wataru Kambara, Shiori Kawamura, Atsushi Kimura, Masaaki Kitaguchi, Ryuju Kobayashi, Takahiro Okamura, Takayuki Oku, Takuya Okudaira, Mao Okuizumi, J. G. Otero Munoz, Joseph D. Parker, Kenji Sakai, Tatsushi Shima, Hirohiko M. …

First Constraint on P-odd/T-odd Cross Section in Polarized Neutron Transmission through Transversely Polarized $^{139}$La
We report the first constraint on time-reversal invariance violating (TRIV) effects in polarized neutron transmission through a polarized $^{139}$La target. Using the explicit forward scattering amplitude for $^{139}$La, we derive analytic expressions for spin observables within the density matrix formalism and apply them to the existing transmission data. The experiment was not optimized for TRIV observables but was taken to measure the spin-dependent cross section around the $p$-wave resonanc…

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations
Fengran Mo, Yifan Gao, Chuan Meng, Xin Liu, Zhuofeng Wu, Kelong Mao, Zhengyang Wang, Pei Chen, Zheng Li, Xian Li, Bing Yin, Meng Jiang
https://arxiv.org/abs/2507.07030

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations
The rapid advancement of conversational search systems revolutionizes how information is accessed by enabling the multi-turn interaction between the user and the system. Existing conversational search systems are usually built with two different models. This separation restricts the system from leveraging the intrinsic knowledge of the models simultaneously, which cannot ensure the effectiveness of retrieval benefiting the generation. The existing studies for developing unified models cannot fu…

A unified model for linear responses of physical networks
Jos\'e M. Ortiz-Tav\'arez, William Stephenson, Xiaoming Mao
https://arxiv.org/abs/2508.04616 https://

A unified model for linear responses of physical networks
Many physical systems--from mechanical lattices and electrical circuits to biological tissues and architected metamaterials--can be understood as networks transmitting physical quantities. We present a unified mathematical framework for describing linear responses of such physical networks using tools from algebraic graph theory. This approach captures static and dynamic behaviors across multiple domains, including mechanical, electrical, thermal, and diffusive responses using node and edge var…

Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition
Wule Mao, Zhouheng Li, Yunhao Luo, Yilun Du, Lei Xie
https://arxiv.org/abs/2507.04384

Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition
Safe trajectory planning remains a significant challenge in complex environments, where traditional methods often trade off computational efficiency for safety. Comprehensive obstacle modeling improves safety but is computationally expensive, while approximate methods are more efficient but may compromise safety. To address this issue, this paper introduces a rapid and safe trajectory planning framework based on state-based diffusion models. Leveraging only low-dimensional vehicle states, the d…

Signature of gate tunable superconducting network in twisted bilayer graphene
Yingbo Wang, Yingzhuo Han, Lu Cao, Xun-Jiang Luo, Yucheng Xue, Jiefei Shi, Xiaomeng Wang, Xiangjia Bai, Junnan Jiang, Ziyi Tian, Kenji Watanabe, Takashi Taniguchi, Fengcheng Wu, Qing-feng Sun, Hong-Jun Gao, Yuhang Jiang, Jinhai Mao
https://arxiv.org/ab…

Signature of gate tunable superconducting network in twisted bilayer graphene
Twisted van der Waals materials provide a tunable platform for investigating two-dimensional superconductivity and quantum phases. Using spectra-imaging scanning tunneling microscopy, we study the superconducting states in twisted bilayer graphene and track their evolution from insulating phases. Gate-dependent spectroscopic measurements reveal two distinct regimes: under-doped (ν = -2.3) and optimally doped (ν = -2.6). In the under-doped regime, partial superconductivity arises, forming a ne…

Fully Integrated Memristive Spiking Neural Network with Analog Neurons for High-Speed Event-Based Data Processing
Zhu Wang, Song Wang, Zhiyuan Du, Ruibin Mao, Yu Xiao, Hayden Kwok-Hay So, Peng Lin, Can Li
https://arxiv.org/abs/2509.04960

Fully Integrated Memristive Spiking Neural Network with Analog Neurons for High-Speed Event-Based Data Processing
The demand for edge artificial intelligence to process event-based, complex data calls for hardware beyond conventional digital, von-Neumann architectures. Neuromorphic computing, using spiking neural networks (SNNs) with emerging memristors, is a promising solution, but existing systems often discard temporal information, demonstrate non-competitive accuracy, or rely on neuron designs with large capacitors that limit the scalability and processing speed. Here we experimentally demonstrate a fu…

FlashRecovery: Fast and Low-Cost Recovery from Failures for Large-Scale Training of LLMs
Haijun Zhang, Jinxiang Wang, Zhenhua Yu, Yanyong Zhang, Xuejie Ji, Kaining Mao, Jun Zhang, Yaqing Zhang, Ting Wu, Fei Jie, Xiemin Huang, Zhifang Cai, Junhua Cheng, Shuwei Wang, Wei Li, Xiaoming Bao, Hua Xu, Shixiong Zhao, Jun Li, Hongwei Sun, Ziyang Zhang, Yi Xiong, Chunsheng Li

FlashRecovery: Fast and Low-Cost Recovery from Failures for Large-Scale Training of LLMs
Large language models (LLMs) have made a profound impact across various fields due to their advanced capabilities. However, training these models at unprecedented scales requires extensive AI accelerator clusters and sophisticated parallelism strategies, which pose significant challenges in maintaining system reliability over prolonged training periods. A major concern is the substantial loss of training time caused by inevitable hardware and software failures. To address these challenges, we p…

Single spin asymmetry $A _ { U L } ^ { \sin ( 3 \phi _ { h } - \phi_{ R } ) }$ in dihadron production in SIDIS
Lei Tan, Gang Li, Mao Song, Xuan Luo
https://arxiv.org/abs/2509.04033

Single spin asymmetry $A _ { U L } ^ { \sin ( 3 ϕ_ { h } - ϕ_{ R } ) }$ in dihadron production in SIDIS
In the field of particle physics, the phenomenon of dihadron production in semi-inclusive deep inelastic scattering (SIDIS) process has always been a significant focus. This paper focuses on the single longitudinal spin asymmetry $A_{UL }^{\sin(3ϕ_{h}-ϕ_{R})}$ in the dihadron production during this process and combines the transverse-momentum-dependent dihadron fragmentation function (DiFF) $H_1^{\perp}$ to deeply analyze its underlying mechanism. Here, the involved DiFF $H_1^{\perp}$ is the …

A note on the Greek letter elements of the homotopy of the $L_n$-local spheres
Ryo Kato, Katsumi Shimomura, Mao-no-suke Shimomura
https://arxiv.org/abs/2507.02155

A note on the Greek letter elements of the homotopy of the $L_n$-local spheres
Let $BP$ denote the Brown-Peterson spectrum at a prime $p$, whose homotopy groups are isomorphic to the polynomial algebra generated by elements $v_i$'s for $i\ge 1$. We consider the homotopy groups of the $v_n^{-1}BP$-localized sphere spectrum $L_nS^0$ with $n^2\le 2p-1$, and show that the groups contain the $n$-th Greek letter family. For the proof of this, we further show the existence of the $v_n^{-1}BP$-localized Smith-Toda spectrum $W_n$ for the case $n^2\le 2p-1$. If the Smith-Toda spect…

Ashton Jeanty, Maxx Crosby, Brock Bowers, Jakobi Meyers and Isaiah Pola-Mao Scrums https://www.raiders.com/video/ashton-jeanty-maxx-crosby-brock-bowers-jakobi-meyers-isaiah-pola-mao-scrums-week-1

Absence of dissipation-free topological edge states in quadratic open fermions
Liang Mao
https://arxiv.org/abs/2508.03821 https://arxiv.org/pdf/2508.03821

Absence of dissipation-free topological edge states in quadratic open fermions
We prove a no-go theorem that generic quadratic open fermionic systems, governed by Lindblad master equations, cannot host dissipation-free topological edge states. Drawing an analogy to topological insulators and superconductors, we map the Lindbladian to a first-quantized matrix representation that encodes the band structure, whose zero-energy topological edge modes are exactly dissipation-free. This matrix, however, is always adiabatically connected to a topologically trivial matrix, even un…

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies
Yaoqi Huang, Julie Stephany Berrio, Mao Shan, Stewart Worrall
https://arxiv.org/abs/2507.06513

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies
Advances in vision-based sensors and computer vision algorithms have significantly improved the analysis and understanding of traffic scenarios. To facilitate the use of these improvements for road safety, this survey systematically categorizes the critical elements that demand attention in traffic scenarios and comprehensively analyzes available vision-driven tasks and datasets. Compared to existing surveys that focus on isolated domains, our taxonomy categorizes attention-worthy traffic entit…

What a beautiful smile has the Japanese 🇯🇵 climber Mao Nakamura 🧗‍♀️. I hold an extra pair of fingers crossed 🤞 for her to top just to see her smile. Not to mention that she keeps smiling

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Accurate and scalable deep Maxwell solvers using multilevel iterative methods
Chenkai Mao, Jonathan A. Fan

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial
Bisheng Wei, Ruihong Jiang, Ruichen Zhang, Yinqiu Liu, Dusit Niyato, Yaohua Sun, Yang Lu, Yonghui Li, Shiwen Mao, Chau Yuen, Marco Di Renzo, Mugen Peng
https://arxiv.org/abs/2509.05946

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial
The rapid advancement toward sixth-generation (6G) wireless networks has significantly intensified the complexity and scale of optimization problems, including resource allocation and trajectory design, often formulated as combinatorial problems in large discrete decision spaces. However, traditional optimization methods, such as heuristics and deep reinforcement learning (DRL), struggle to meet the demanding requirements of real-time adaptability, scalability, and dynamic handling of user inte…

Generative Auto-Bidding in Large-Scale Competitive Auctions via Diffusion Completer-Aligner
Yewen Li, Jingtong Gao, Nan Jiang, Shuai Mao, Ruyi An, Fei Pan, Xiangyu Zhao, Bo An, Qingpeng Cai, Peng Jiang
https://arxiv.org/abs/2509.03348

Generative Auto-Bidding in Large-Scale Competitive Auctions via Diffusion Completer-Aligner
Auto-bidding is central to computational advertising, achieving notable commercial success by optimizing advertisers' bids within economic constraints. Recently, large generative models show potential to revolutionize auto-bidding by generating bids that could flexibly adapt to complex, competitive environments. Among them, diffusers stand out for their ability to address sparse-reward challenges by focusing on trajectory-level accumulated rewards, as well as their explainable capability, i.e.,…

Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams
Wenxin Mao, Zhitao Wang Long Wang, Sirong Chen, Cuiyun Gao, Luyang Cao, Ziming Liu, Qiming Zhang, Jun Zhou, Zhi Jin
https://arxiv.org/abs/2508.03379

Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams
Large language models (LLMs) excel at generating code from natural language (NL) descriptions. However, the plain textual descriptions are inherently ambiguous and often fail to capture complex requirements like intricate system behaviors, conditional logic, and architectural constraints; implicit data dependencies in service-oriented architectures are difficult to infer and handle correctly. To bridge this gap, we propose a novel step-by-step code generation framework named UML2Dep by leveragi…

CSRM-LLM: Embracing Multilingual LLMs for Cold-Start Relevance Matching in Emerging E-commerce Markets
Yujing Wang, Yiren Chen, Huoran Li, Chunxu Xu, Yuchong Luo, Xianghui Mao, Cong Li, Lun Du, Chunyang Ma, Qiqi Jiang, Yin Wang, Fan Gao, Wenting Mo, Pei Wen, Shantanu Kumar, Taejin Park, Yiwei Song, Vijay Rajaram, Tao Cheng, Sonu Durgia, Pranam Kolari
https://…

CSRM-LLM: Embracing Multilingual LLMs for Cold-Start Relevance Matching in Emerging E-commerce Markets
As global e-commerce platforms continue to expand, companies are entering new markets where they encounter cold-start challenges due to limited human labels and user behaviors. In this paper, we share our experiences in Coupang to provide a competitive cold-start performance of relevance matching for emerging e-commerce markets. Specifically, we present a Cold-Start Relevance Matching (CSRM) framework, utilizing a multilingual Large Language Model (LLM) to address three challenges: (1) activati…

Near-Field ISAC for THz Wireless Systems
Fan Zhang, Tianqi Mao, Mingkun Li, Meng Hua, Jinshu Chen, Christos Masouros, Zhaocheng Wang
https://arxiv.org/abs/2507.04292

Near-Field ISAC for THz Wireless Systems
Sixth-generation (6G) wireless networks are expected not only to provide high-speed connectivity but also to support reliable sensing capabilities, giving rise to the integrated sensing and communication (ISAC) paradigm. To enable higher data rates and more accurate sensing, terahertz (THz) systems empowered by extremely large multiple-input-multiple-output (XL-MIMO) technology are envisioned as key enablers for future ISAC systems. Owing to the substantial increase in both effective array aper…

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
- MARS: Processing-In-Memory Acceleration of Raw Signal Genome Analysis Inside the Storage Subsystem
Soysal, Koliogeorgi, Firtina, Ghiasi, Nadig, Mao, Oliveira, Liang, Zambaku, Sadrosadati, Mutlu
…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[5/5]:
- IntuiTF: MLLM-Guided Transfer Function Optimization for Direct Volume Rendering
Wang, Pan, Wang, Liu, Mao, Liu, Zhu, Huang, Chen, Zhang, Chen

Anomalous Magnetoresistance Beyond the Julli\`ere Model for Spin Selectivity in Chiral Molecules
Tian-Yi Zhang, Yue Mao, Ai-Min Guo, Qing-Feng Sun
https://arxiv.org/abs/2509.05588

Anomalous Magnetoresistance Beyond the Jullière Model for Spin Selectivity in Chiral Molecules
The issue of anomalous high magnetoresistance, beyond the Jullière model, observed in nonmagnetic electrode-chiral molecular-ferromagnetic electrode devices has puzzled the community for a long time. Here, by considering the magnetic proximity effect which shifts the nonmagnetic-ferromagnetic interface toward chiral molecules, we show the anomalous high magnetoresistance beyond the spin polarization in ferromagnetic electrodes even in the very weak spin-orbit coupling. Our results are in excel…

Attention-Guided Multi-Scale Local Reconstruction for Point Clouds via Masked Autoencoder Self-Supervised Learning
Xin Cao, Haoyu Wang, Yuzhu Mao, Xinda Liu, Linzhi Su, Kang Li
https://arxiv.org/abs/2507.04084

Attention-Guided Multi-Scale Local Reconstruction for Point Clouds via Masked Autoencoder Self-Supervised Learning
Self-supervised learning has emerged as a prominent research direction in point cloud processing. While existing models predominantly concentrate on reconstruction tasks at higher encoder layers, they often neglect the effective utilization of low-level local features, which are typically employed solely for activation computations rather than directly contributing to reconstruction tasks. To overcome this limitation, we introduce PointAMaLR, a novel self-supervised learning framework that enha…

Hunyuan-MT Technical Report
Mao Zheng, Zheng Li, Bingxin Qu, Mingyang Song, Yang Du, Mingrui Sun, Di Wang
https://arxiv.org/abs/2509.05209 https://arxiv.or…

Hunyuan-MT Technical Report
In this report, we introduce Hunyuan-MT-7B, our first open-source multilingual translation model, which supports bidirectional translation across 33 major languages and places a special emphasis on translation between Mandarin and several ethnic minority languages as well as dialects. Furthermore, to serve and address diverse translation scenarios and enhance model performance at test time, we introduce Hunyuan-MT-Chimera-7B, a translation model inspired by the slow thinking mode. This model in…

SAT-BO: Verification Rule Learning and Optimization for FraudTransaction Detection
Mao Luo, Zhi Wang, Yiwen Huang, Qingyun Zhang, Zhouxing Su, Zhipeng Lv, Wen Hu, Jianguo Li
https://arxiv.org/abs/2507.02635

SAT-BO: Verification Rule Learning and Optimization for FraudTransaction Detection
Electronic payment platforms are estimated to process billions oftransactions daily, with the cumulative value of these transactionspotentially reaching into the trillions. Even a minor error within thishigh-volume environment could precipitate substantial financiallosses. To mitigate this risk, manually constructed verification rules,developed by domain experts, are typically employed to identifyand scrutinize transactions in production environments. However,due to the absence of a systematic …

Whatever success Trump had in his career was built on insight
-- not into the workings of capitalism but into the darker corners of human nature.
He succeeded through scams, lies, and bullying,
using the power he had over others to enrich himself at their expense.
So no one should be surprised that he brings the same spirit to policymaking.
In his second term, Trump is at last unleashed to fully realize his vision,
and on economics, that means a new kind…

Chairman Trump's Great Grift Forward
Move over, Mao.

Towed Movable Antenna (ToMA) Array for Ultra Secure Airborne Communications
Lipeng Zhu, Haobin Mao, Wenyan Ma, Zhenyu Xiao, Jun Zhang, Rui Zhang
https://arxiv.org/abs/2508.01229

Towed Movable Antenna (ToMA) Array for Ultra Secure Airborne Communications
This paper proposes a novel towed movable antenna (ToMA) array architecture to enhance the physical layer security of airborne communication systems. Unlike conventional onboard arrays with fixed-position antennas (FPAs), the ToMA array employs multiple subarrays mounted on flexible cables and towed by distributed drones, enabling agile deployment in three-dimensional (3D) space surrounding the central aircraft. This design significantly enlarges the effective array aperture and allows dynamic …

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Towards Explainable Vulnerability Detection with Large Language Models
Qiheng Mao, Zhenhao Li, Xing Hu, Kui Liu, Xin Xia, Jianling Sun

'Always the best feeling': Raiders' explosive plays lead to Week https://www.raiders.com/video/maxx-crosby-isaiah-pola-mao-postgame-recap-win-nfl-week-1-patriots-2025

SQUASH: A SWAP-Based Quantum Attack to Sabotage Hybrid Quantum Neural Networks
Rahul Kumar, Wenqi Wei, Ying Mao, Junaid Farooq, Ying Wang, Juntao Chen
https://arxiv.org/abs/2506.24081

SQUASH: A SWAP-Based Quantum Attack to Sabotage Hybrid Quantum Neural Networks
We propose a circuit-level attack, SQUASH, a SWAP-Based Quantum Attack to sabotage Hybrid Quantum Neural Networks (HQNNs) for classification tasks. SQUASH is executed by inserting SWAP gate(s) into the variational quantum circuit of the victim HQNN. Unlike conventional noise-based or adversarial input attacks, SQUASH directly manipulates the circuit structure, leading to qubit misalignment and disrupting quantum state evolution. This attack is highly stealthy, as it does not require access to t…

LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence
Xingxuan Zhang, Gang Ren, Han Yu, Hao Yuan, Hui Wang, Jiansheng Li, Jiayun Wu, Lang Mo, Li Mao, Mingchao Hao, Ningbo Dai, Renzhe Xu, Shuyang Li, Tianyang Zhang, Yue He, Yuanrui Wang, Yunjia Zhang, Zijing Xu, Dongzhe Li, Fang Gao, Hao Zou, Jiandong Liu, Jiashuo Liu, Jiawei Xu, Kaijie Cheng, Kehan Li, Linjun Zhou, Qing Li, Shaohua Fan, Xiaoyu Lin, Xinyan Han, Xuanyue Li, Yan Lu, Yuan Xue, Yuanyuan Jiang, Zi…

LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence
We argue that progress toward general intelligence requires complementary foundation models grounded in language, the physical world, and structured data. This report presents LimiX, the first installment of our large structured-data models (LDMs). LimiX treats structured data as a joint distribution over variables and missingness, thus capable of addressing a wide range of tabular tasks through query-based conditional prediction via a single model. LimiX is pretrained using masked joint-distri…

Efficient spin-pumping and spin-to-charge conversion in epitaxial Mn$_3$Sn(0001) noncollinear antiferromagnetic films
Surya N. Panda, Ning Mao, Nikolai Peshcherenko, Xiaolong Feng, Yang Zhang, Anastasios Markou, Claudia Felser, Edouard Lesne
https://arxiv.org/abs/2508.02415

Efficient spin-pumping and spin-to-charge conversion in epitaxial Mn$_3$Sn(0001) noncollinear antiferromagnetic films
The generation and control of spin currents are crucial for advancing next-generation spintronic technologies. These technologies depend on materials capable of efficiently sourcing and interconverting spin and charge currents, while overcoming some limitations associated with conventional ferromagnets and heavy metals. Kagome topological antiferromagnetic Weyl semimetals, such as Mn$_3$Sn, present unique advantages owing to their distinct magnetic order and significant Berry curvature-driven t…

Jakobi Meyers, Dont'e Thornton Jr., Michael Mayer and Isaiah Pola-Mao Scrums | Week 2 vs. Chargers https://www.youtube.com/watch?v=csQmPA7iess

Orbital hybridization in graphene-based artificial atoms
Yue Mao, Hui-Ying Ren, Xiao-Feng Zhou, Hao Sheng, Yun-Hao Xiao, Yu-Chen Zhuang, Ya-Ning Ren, Lin He, Qing-Feng Sun
https://arxiv.org/abs/2509.04012

Orbital hybridization in graphene-based artificial atoms
Intraatomic orbital hybridization and interatomic bond formation are the two fundamental processes when real atoms are condensed to form matter. Artificial atoms mimic real atoms by demonstrating discrete energy levels attributable to quantum confinement. As such, they offer a solid-state analogue for simulating intraatomic orbital hybridization and interatomic bond formation. Signatures of interatomic bond formation has been extensively observed in various artificial atoms. However, direct evi…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[2/3]:
- Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimization
Guo, Liu, Chen, Mao, Hu, Jiang, Yu, Xu, Liu, Xu, Chen, Guo

YOLO-based Bearing Fault Diagnosis With Continuous Wavelet Transform
Po-Heng Chou, Wei-Lung Mao, Ru-Ping Lin
https://arxiv.org/abs/2509.03070 https://arxiv…

YOLO-based Bearing Fault Diagnosis With Continuous Wavelet Transform
This letter proposes a YOLO-based framework for spatial bearing fault diagnosis using time-frequency spectrograms derived from continuous wavelet transform (CWT). One-dimensional vibration signals are first transformed into time-frequency spectrograms using Morlet wavelets to capture transient fault signatures. These spectrograms are then processed by YOLOv9, v10, and v11 models to classify fault types. Evaluated on three benchmark datasets, including Case Western Reserve University (CWRU), Pad…

Isaiah Pola-Mao looks to bring physicality in the secondary https://www.raiders.com/video/isaiah-pola-mao-defense-secondary-nfl-07272025

OmniD: Generalizable Robot Manipulation Policy via Image-Based BEV Representation
Jilei Mao, Jiarui Guan, Yingjuan Tang, Qirui Hu, Zhihang Li, Junjie Yu, Yongjie Mao, Yunzhe Sun, Shuang Liu, Xiaozhu Ju
https://arxiv.org/abs/2508.11898

OmniD: Generalizable Robot Manipulation Policy via Image-Based BEV Representation
The visuomotor policy can easily overfit to its training datasets, such as fixed camera positions and backgrounds. This overfitting makes the policy perform well in the in-distribution scenarios but underperform in the out-of-distribution generalization. Additionally, the existing methods also have difficulty fusing multi-view information to generate an effective 3D representation. To tackle these issues, we propose Omni-Vision Diffusion Policy (OmniD), a multi-view fusion framework that synthe…

Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science
Rui Mao, Qian Liu, Xiao Li, Erik Cambria, Amir Hussain
https://arxiv.org/abs/2508.20674 https://…

Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science
Cognitive Science has profoundly shaped disciplines such as Artificial Intelligence (AI), Philosophy, Psychology, Neuroscience, Linguistics, and Culture. Many breakthroughs in AI trace their roots to cognitive theories, while AI itself has become an indispensable tool for advancing cognitive research. This reciprocal relationship motivates a comprehensive review of the intersections between AI and Cognitive Science. By synthesizing key contributions from both perspectives, we observe that AI pr…

Universal Quantum Computational Spectroscopy on a Quantum Chip
Chonghao Zhai, Jinzhao Sun, Jieshan Huang, Jun Mao, Hongchang Bao, Siyuan Zhang, Qihuang Gong, Vlatko Vedral, Xiao Yuan, Jianwei Wang
https://arxiv.org/abs/2506.22418

Universal Quantum Computational Spectroscopy on a Quantum Chip
Spectroscopy underpins modern scientific discovery across diverse disciplines. While experimental spectroscopy probes material properties through scattering or radiation measurements, computational spectroscopy combines theoretical models with experimental data to predict spectral properties, essential for advancements in physics, chemistry, and materials science. However, quantum systems present unique challenges for computational spectroscopy due to their inherent complexity, and current quan…

Spin Splitting Nernst Effect in Altermagnet
Xing-Jian Yi, Yue Mao, Xiancong Lu, Qing-Feng Sun
https://arxiv.org/abs/2509.03822 https://arxiv.org/pdf/2509.0…

Spin Splitting Nernst Effect in Altermagnet
Altermagnet is a distinctive magnet phase, which has spin-split energy band but with zero net magnetic moment. In this paper, we propose that altermagnet behaves spin splitting Nernst effect: Under a longitudinal temperature gradient, the electrons with opposite spins tend to split oppositely in the transverse direction, thus generating a transverse spin current. The spin splitting Nernst effect is understood from the contribution of the longitudinal wave vector to the transverse group velocity…

DepthGait: Multi-Scale Cross-Level Feature Fusion of RGB-Derived Depth and Silhouette Sequences for Robust Gait Recognition
Xinzhu Li, Juepeng Zheng, Yikun Chen, Xudong Mao, Guanghui Yue, Wei Zhou, Chenlei Lv, Ruomei Wang, Fan Zhou, Baoquan Zhao
https://arxiv.org/abs/2508.03397

DepthGait: Multi-Scale Cross-Level Feature Fusion of RGB-Derived Depth and Silhouette Sequences for Robust Gait Recognition
Robust gait recognition requires highly discriminative representations, which are closely tied to input modalities. While binary silhouettes and skeletons have dominated recent literature, these 2D representations fall short of capturing sufficient cues that can be exploited to handle viewpoint variations, and capture finer and meaningful details of gait. In this paper, we introduce a novel framework, termed DepthGait, that incorporates RGB-derived depth maps and silhouettes for enhanced gait r…

Raiders Who Will Earn Expanded Roles in 2025 https://www.si.com/nfl/raiders/las-vegas-tyree-wilson-decamerion-richardson-isaiah-pola-mao

Interference Management for Integrated Sensing and Communications: A Multiple Access Perspective
Kexin Chen, Yijie Mao, Wonjae Shin, Bruno Clerckx, Christos Masouros
https://arxiv.org/abs/2509.02352

Interference Management for Integrated Sensing and Communications: A Multiple Access Perspective
The integrated sensing and communication (ISAC) technique has been considered a key enabler for 6G radio access networks. ISAC fulfills a brand new paradigm shift in wireless networks via the seamless interplay between communication and sensing within a unified network. However, the tight integration of these functionalities inevitably gives rise to various types of interference, posing significant challenges to existing ISAC waveform designs and rendering interference management a critical con…

Tunneling Magnetoresistance Effect in Altermagnets
Yu-Fei Sun, Yue Mao, Yu-Chen Zhuang, Qing-Feng Sun
https://arxiv.org/abs/2509.04015 https://arxiv.org/pd…

Tunneling Magnetoresistance Effect in Altermagnets
As an unconventional magnet, altermagnetism attracts great interest in condensed matter physics and applies a new research platform for the spintronics. Since the tunneling magnetoresistance (TMR) effect is an important research aspect in spintronics, we theoretically propose a universal altermagnetic sandwich device to achieve the TMR effect and investigate its transport properties. Using the nonequilibrium Green's function method and the Landauer-Büttiker formula, we obtain the conductance a…

Noisy Label Refinement with Semantically Reliable Synthetic Images
Yingxuan Li, Jiafeng Mao, Yusuke Matsui
https://arxiv.org/abs/2509.04298 https://arxiv.o…

Noisy Label Refinement with Semantically Reliable Synthetic Images
Semantic noise in image classification datasets, where visually similar categories are frequently mislabeled, poses a significant challenge to conventional supervised learning approaches. In this paper, we explore the potential of using synthetic images generated by advanced text-to-image models to address this issue. Although these high-quality synthetic images come with reliable labels, their direct application in training is limited by domain gaps and diversity constraints. Unlike convention…

A Novel Evaluation Benchmark for Medical LLMs: Illuminating Safety and Effectiveness in Clinical Domains
Shirui Wang, Zhihui Tang, Huaxia Yang, Qiuhong Gong, Tiantian Gu, Hongyang Ma, Yongxin Wang, Wubin Sun, Zeliang Lian, Kehang Mao, Yinan Jiang, Zhicheng Huang, Lingyun Ma, Wenjie Shen, Yajie Ji, Yunhui Tan, Chunbo Wang, Yunlu Gao, Qianling Ye, Rui Lin, Mingyu Chen, Lijuan Niu, Zhihao Wang, Peng Yu, Mengran Lang, Yue Liu, Huimin Zhang, Haitao Shen, Long Chen, Qiguang Zhao, Si-Xuan Liu…

A Novel Evaluation Benchmark for Medical LLMs: Illuminating Safety and Effectiveness in Clinical Domains
Large language models (LLMs) hold promise in clinical decision support but face major challenges in safety evaluation and effectiveness validation. We developed the Clinical Safety-Effectiveness Dual-Track Benchmark (CSEDB), a multidimensional framework built on clinical expert consensus, encompassing 30 criteria covering critical areas like critical illness recognition, guideline adherence, and medication safety, with weighted consequence measures. Thirty-two specialist physicians developed an…

Phase transitions in quantum dot-Majorana zero mode coupling systems
Yue Mao, Qing-Feng Sun
https://arxiv.org/abs/2509.04002 https://arxiv.org/pdf/2509.040…

Phase transitions in quantum dot-Majorana zero mode coupling systems
The magnetic doublet ground state (GS) of a quantum dot (QD) could be changed to a spin-singlet GS by coupling to a superconductor. In analogy, here we study the GS phase transitions in QD-Majorana zero mode (MZM) coupling systems: GS behaves phase transition versus intra-dot energy level and QD-MZM coupling strength. The phase diagrams of GS are obtained, for cases with and without Zeeman term. Along with the phase transition, we also study the change of spin feature and density of states. The…

Defensive Player Likes The Energy That Raiders HC Carroll Brings https://www.si.com/nfl/raiders/las-vegas-pete-carroll-isaiah-pola-mao-patrick-graham-training-camp

LongAnimation: Long Animation Generation with Dynamic Global-Local Memory
Nan Chen, Mengqi Huang, Yihao Meng, Zhendong Mao
https://arxiv.org/abs/2507.01945

LongAnimation: Long Animation Generation with Dynamic Global-Local Memory
Animation colorization is a crucial part of real animation industry production. Long animation colorization has high labor costs. Therefore, automated long animation colorization based on the video generation model has significant research value. Existing studies are limited to short-term colorization. These studies adopt a local paradigm, fusing overlapping features to achieve smooth transitions between local segments. However, the local paradigm neglects global information, failing to maintai…

Carroll's Excitement About One Position Group Continues to Increase https://www.si.com/nfl/raiders/las-vegas-eric-stokes-pete-carroll-jeremy-chinn-isaiah-pola-mao

Atomic collapse of high-order singular potentials in graphene
Yu-Chen Zhuang, Yue Mao, Qing-Feng Sun
https://arxiv.org/abs/2509.03921 https://arxiv.org/pdf…

Atomic collapse of high-order singular potentials in graphene
Artificial atoms in graphene hosting a series of quasi-bound states can serve as an excellent platform to explore atomic collapse and become a basis to design novel graphene nanodevices. We theoretically study behaviors of massless Dirac fermions in singular potentials with a general form of 1/r^γ. Different from the Coulomb potential that demands a supercritical charge Z > Zc, a high-order singular potential (γ > 1) is found to in principle induce atomic collapse with an infinitesimal charge…

Raiders Defender Knows About Earning Respect https://www.si.com/nfl/raiders/las-vegas-isaiah-pola-mao-training-camp-patrick-graham

Kwai Keye-VL Technical Report
Kwai Keye Team, Biao Yang, Bin Wen, Changyi Liu, Chenglong Chu, Chengru Song, Chongling Rao, Chuan Yi, Da Li, Dunju Zang, Fan Yang, Guorui Zhou, Hao Peng, Haojie Ding, Jiaming Huang, Jiangxia Cao, Jiankang Chen, Jingyun Hua, Jin Ouyang, Kaibing Chen, Kaiyu Jiang, Kaiyu Tang, Kun Gai, Shengnan Zhang, Siyang Mao, Sui Huang, Tianke Zhang, Tingting Gao, Wei Chen, Wei Yuan, Xiangyu Wu, Xiao Hu, Xingyu Lu, Yang Zhou, Yi-Fan Zhang, Yiping Yang, Yulong Chen, Zhenh…

Kwai Keye-VL Technical Report
While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities on static images, they often fall short in comprehending dynamic, information-dense short-form videos, a dominant medium in today's digital landscape. To bridge this gap, we introduce \textbf{Kwai Keye-VL}, an 8-billion-parameter multimodal foundation model engineered for leading-edge performance in short-video understanding while maintaining robust general-purpose vision-language abilities. The development of Ke…

This Pola-Mao pick 😮‍💨 https://www.youtube.com/shorts/r0-x2HQIqMg

WATCH: Raiders Quarterback Geno Smith Speaks Following Training Camp https://www.si.com/nfl/raiders/las-vegas-training-camp-pete-carroll-isaiah-pola-mao-

Ashton Jeanty, Maxx Crosby, Brock Bowers, Jakobi Meyers and Isaiah Pola-Mao Postgame Media | Week 1 https://www.youtube.com/watch?v=1lw_0j0hxwg

Will Jamal Adams Return to Form with Raiders? https://www.si.com/nfl/raiders/las-vegas-jamal-adams-jeremy-chinn-isaiah-pola-mao-pete-carroll-

Rising Raiders Defender is Ready to Take the Next Step https://www.si.com/nfl/raiders/las-vegas-pete-carroll-isaiah-pola-mao-eric-stokes-jeremy-chinn

Raiders Veteran Will Not be Under-the-Radar for Long https://www.si.com/nfl/raiders/news/pete-carroll-jeremy-chinn-washington-commanders-patrick-graham-isaiah-pola-mao

How Many Safeties Will Make Raiders' Roster? https://www.si.com/nfl/raiders/las-vegas-trey-taylor-thomas-harper-isaiah-pola-mao-chris-smith

Raiders' Safety Position in Good Shape Heading into Season https://www.si.com/nfl/raiders/isaiah-pola-mao-las-vegas-training-camp-chris-smith-jeremy-chinn

2025 Position Breakdown: Identity of Raiders secondary revealing itself throughout offseason https://www.raiders.com/news/2025-position-breakdown-cornerbacks-safeties-jeremy-chinn-jakorian-bennett-isaiah-pola-mao