HazardWeaver is an AI agent designed to select and execute appropriate scientific methods for hazard analysis by leveraging a Hazard Knowledge Compiler and a Hazard Capability Graph. It dynamically revises its route choices as new evidence and execution results emerge, ensuring that selected methods are both applicable and executable with available data and tools. The system is evaluated on the Hazard Weaver Benchmark, which includes 141 instances across multiple hazard domains, and demonstrates superior performance over existing agent systems, especially when multiple scientific routes are viable.
By Wangshu Zhu, Xueqi Cheng, Liang Wu, Yushun Dong
Page-EntroKV is a new KV‑cache eviction framework designed for grouped‑query attention (GQA) in long‑context autoregressive language models. It pools token importance scores across query heads within each physical group using sink‑isolated Renyi‑2 entropy, then projects these pooled scores onto page frames and performs eviction at the hardware tuple level. The authors prove theoretical guarantees on union overhead, budget preservation, and needle‑retention, and demonstrate on a Qwen2.5‑1.5B‑Instruct pilot that Page‑EntroKV achieves exact union overhead control, eliminates sink masquerade, and retains 100% of critical tokens compared to mean‑pooling baselines.
By Inbasekaran S
arXiv:2610.03551v1 Announce Type: new
Abstract: Large language models (LLMs) have reached expert-level performance on competition mathematics largely through the volume of search placed around them:...
By Yanli Wang, Suijin Wang, Xiaopeng Yuan, Haohan Wang
arXiv:2607.00711v2 Announce Type: cross
Abstract: Large Language Models have emerged as programming assistants. However, the efficacy of code generation is constrained by the quality of input require...
By Zheng Fang, Dongming Jin, Yihong dong, Yongmin Li, Kechi Zhang, Zhi Jin, Ge Li
arXiv:2610.02359v1 Announce Type: cross
Abstract: Reinforcement learning from verifiable rewards (RLVR) usually optimizes answer correctness, yet useful language-model behavior also requires high-qua...
By Doseok Jang, Jon Ander Campos, Youran Qi
arXiv:2610.03702v1 Announce Type: new
Abstract: The choice of post-training data for large language models substantially affects downstream performance. Gradient-based data selection is a popular app...
By Lyuxin David Zhang, Eric Wong, Surbhi Goel, Anton Xue
arXiv:2610.02214v1 Announce Type: cross
Abstract: Ship structures govern vessel strength, safety, and manufacturability, but their design must satisfy hundreds of classification society requirements,...
By Noah J. Bagazinski, Md. Ferdous Alam, Jaya Manideep Rebbagondla, Faez Ahmed
arXiv:2610.03089v1 Announce Type: cross
Abstract: Modern Computer Use Agents (CUAs) directly interact with graphical user interfaces and execute third-party web tools, exposing them to indirect promp...
By Giulio Zingrillo, Hanna Foerster, Ilia Shumailov, Yiren Zhao, Robert Mullins
arXiv:2610.03102v1 Announce Type: cross
Abstract: An LLM agent can recognize uncertainty yet still choose the wrong next step: asking when action is already justified, or seeking clarification when t...
By Ang Li, Yue Lin, Feifei Kou, Zhan Su, Prayag Tiwari, Wenhao Li, Shuhui Zhu, Hongyuan Zha, Baoxiang Wang
arXiv:2610.03123v1 Announce Type: cross
Abstract: Existing streaming vision-language models (VLMs) continuously perceive and reason over visual streams, but their computational pathways remain fixed...
By Ashok Prasad Neupane, Dipan Bartaula, Ankit Belbase, Saugat Adhikari, Samip Ghimire, Saroj Poudel, Binod Bhattarai, Danda Pani Paudel
arXiv:2610.03124v1 Announce Type: cross
Abstract: Open-weight language models can be downloaded, modified, and deployed beyond their developers' control, limiting the effectiveness of centrally enfor...
By Toluwani Aremu, Manit Baser, Mohan Gurusamy, Nils Lukas, Dinil Mon Divakaran
arXiv:2610.03153v1 Announce Type: cross
Abstract: Workspace agents combine large language models with execution harnesses to perform stateful, multi-step tasks that access or modify external resource...
By Shiyi Kuang, Xuemei Luo, Kun Liu, Junhai Li, Rui Tian, Feng Shi, Bo Shen, Nianyu Li, Dehui Li, Ping Chen
arXiv:2610.03190v1 Announce Type: cross
Abstract: Accident, defect and outage investigations end with a decision that ordinary question answering never faces: whether the evidence gathered so far is...
By Tingzhu Bi, Ping Wang, Meng Ma
arXiv:2610.02351v1 Announce Type: new
Abstract: ReAct-based agents typically rely on a single LLM policy to propose actions, interact with the environment, and decide when a task is complete. This co...
By Ajay Vohra, Tao Chen, Neeti Narayan, Caron Zhang
arXiv:2610.02588v1 Announce Type: new
Abstract: Agents are increasingly given open-ended research tasks: discovering an empirical law from self-designed experiments, improving a heuristic whose optim...
By Chengyang Shi, Xianglin Ji, Jintao Huang, Jicheng Wang, Yifeng He, Jiachen Liu
arXiv:2610.03463v1 Announce Type: cross
Abstract: Neural quantum states based on modern deep learning architectures have emerged as powerful representations for quantum many-body systems. In particul...
By Zhen Qin, Qing Qu, Alfred O. Hero III
arXiv:2610.03625v1 Announce Type: cross
Abstract: Relational databases are among the most widely deployed forms of structured knowledge, and natural language access to them requires grounding languag...
By Darian Lee, Shannon Rumsey, Jack St. Clair, Xinyi Tang, Aditya Bansal, Yuanming Shi
arXiv:2610.02638v1 Announce Type: new
Abstract: Full-duplex voice agents make many small, closed decisions, which current systems answer by slow autoregressive decoding. We propose DuplexJev, which f...
By Jie Jin, Ziyin Ma, Min Yin, Jinyu Chen, Haigang Song, Zhikun Pang, Xiaowen Zhang
arXiv:2610.02664v1 Announce Type: new
Abstract: Long-horizon agents are now playing an increasingly significant role in assisting humans with complex problem-solving. However, it is exactly their ext...
By XinPeng Shen, Lan Zhang, Yixiao Huang, Haoran Cheng, Jiewei Lai, Leilei Chen, Haoxiang Deng
arXiv:2610.02679v1 Announce Type: new
Abstract: Data journalism, the practice of using data analysis to surface newsworthy stories, depends increasingly on the ability of reporters and investigative...
By Raquib Bin Yousuf, Harith Laxman, Vitaliy Shkremetko, Eunice Son, Shambhavi Verma, Brian O'Leary, Venketesh Subramony, Sylvain Nazef, Jacquelyn Elias, Ron Coddington, Chris Contakes, Michael Riley, Naren Ramakrishnan