The paper introduces TRACE, a training‑free agent for long‑video understanding that grounds answers in raw visual clips and builds an evidence bundle until the answer stabilises. It also presents VES‑Bench, a 600‑question benchmark over 348 public long videos that audits whether decoded frames cover all necessary evidence intervals at three strictness levels. TRACE achieves high accuracy on VES‑Bench (63.5% audit accuracy) and remains competitive on other video‑understanding benchmarks while using far fewer frames than uniform decoding.
By Pengyiang Liu, Junbo Niu, Xiaoyang Hu, Zhongyue Shi, Zitian Wang, Linjiang Huang, Si Liu
arXiv:2608.23104v1 Announce Type: cross
Abstract: Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or we...
By Jiatong Li, Wengyu Zhang, Weida Wang, Yuxuan Ren, Wei Liu, Chenyang Mao, Yuqiang Li, Yatao Bian, Changmeng Zheng, Xiaoyong Wei, Qing Li
arXiv:2608.22725v1 Announce Type: new
Abstract: Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity ha...
By Jiaqi Liu, Maolin Ran, Xiaoyang Lu, Jian Wang, Weiwen Liu, Jianghao Lin, Yong Yu, Weinan Zhang
arXiv:2608.22899v1 Announce Type: new
Abstract: Unlike static medical question answering, long-horizon diagnosis captures the sequential nature of clinical practice: evidence is progressively acquire...
By Xiwei Dai, Zijie Meng, Zhiting Fan, Yixuan Tang, Ziru Niu, Zuozhu Liu
arXiv:2601.19066v3 Announce Type: replace-cross
Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix ge...
By Runxiang Cheng, Michele Tufano, Jos\'e Cambronero, Renyao Wei, Sherry Shi, Grant Uy, Pat Rondon, Franjo Ivan\v{c}i\'c
arXiv:2608.22971v1 Announce Type: new
Abstract: Embodied Reasoning constitutes a fundamental capability of embodied intelligence, serving as the basis for autonomous perception, reasoning, and intera...
By Min Chen, Shengjun Zhang, Yuxin Li, Zhang Zhang, Xin Fei, Chong Xia, Yueqi Duan
InjecMEM introduces a memory injection attack that can steer the responses of large language model agents toward a desired output using only a single interaction, without needing read or edit access to the memory store. The attack leverages the retrieval‑then‑generate workflow of memory systems by crafting a retriever‑agnostic anchor with high‑recall topical cues and an adversarial command optimized through gradient‑based coordinate search. Experiments across various memory systems and backbone models show that InjecMEM reliably induces topic‑conditioned retrieval and targeted generation, remains effective even when memory drifts, and does not affect non‑target queries.
By Hanling Tian, Gengyu Zhang, Zeyang Sha, Jingying Wang, Yuhang Liu, Zhehao Huang, Kun Yang, Xiaolin Huang
The paper introduces Boundary-Aware Skill Memory (BASM), a method that enriches skill memories for large language model agents with explicit boundary fields such as applicability conditions, risk cues, avoidance rules, and recovery notes. This approach transforms retrieved skills from unconditional templates into state‑conditioned guidance, preventing the Skill Imitation Trap where more skills lead to incorrect tool usage. Experiments on three agent benchmarks and four model scales show that BASM improves task success rates, accuracy, and reduces attack success while cutting average steps compared to memory‑free baselines.
By Zihan Lin, Zhenyu Chen, Jiawen Wei, Xiaohan Wang, Jie Cao, Jiajun Chai, Wei Lin, Guojun Yin, Ran He
WorldMind is a decoupled framework for state-aware NPC behavior in game world models, separating interactive world modeling into four layers: Understanding, Decision, Control, and Generation. It constructs a compact state from generated frames, reasons over it to plan NPC actions, translates actions into temporally aligned conditions, and synthesizes visual outcomes. Experiments on the newly introduced BOSS-140K dataset show that WorldMind achieves more tactically appropriate and coherent NPC behavior than baseline models in about 70% of pairwise comparisons.
By Zhiyang Deng, Boran Zhang, Danze Chen, Yeying Jin
arXiv:2608.21417v1 Announce Type: new
Abstract: Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based wor...
By Zhichao Zhou, Siyuan Chen, Omkar Salunkhe, Ebru Turanoglu Bekar, Johan Stahre, Anders Skoogh
arXiv:2608.22533v1 Announce Type: new
Abstract: Autonomous computer-use agents are increasingly applied to long-horizon tasks requiring coordinated application calls, persistent state tracking, and v...
By Zheyuan Deng, Binghang Lu, Hanqi Feng, Shirley Huang, Dianzhuo Wang, Yuanda Xu, Zhiwei Zhang, Yige Sun, Changhong Mou, Runyu Zhang, Yuexing Hao, Barnabas Poczos, Xiaomin Li
arXiv:2608.22510v1 Announce Type: new
Abstract: Agent benchmarks often evaluate only final answers even when agents run on stateful runtimes. We argue this under-specifies what is being evaluated: th...
By YuanHang Xiao
arXiv:2608.22512v1 Announce Type: new
Abstract: Autonomous multi-agent systems nowadays act in finance, software supply chains, and security operations. Already, the first largely AI-orchestrated int...
By Christos Sardianos, Iliana Pla, Vasilis Efthymiou, Iraklis Varlamis, Thomas Lagkas, Panagiotis Sarigiannidis, Georgios Th. Papadopoulos
arXiv:2608.22538v1 Announce Type: new
Abstract: Policy-governed agents must interpret case evidence while following an authorized procedure. We present \textsc{Stage}, an executable-graph framework t...
By Mengxi Luo, Changjia Chen, An Cao, Zirong Huang, Wanyi Dai
arXiv:2608.22577v1 Announce Type: new
Abstract: Long-horizon GUI agents can retain a complete interaction trace cheaply as textual action records, but expose only a few past events to the policy in h...
By Jiaxuan Luo, Zhanfeng Liao, Jiayao Teng, Yuan Wang, Haojian Huang
arXiv:2608.22615v1 Announce Type: new
Abstract: Large Language Model (LLM)-based counseling agents can generate fluent and supportive responses, but they often lack the structured, goal-directed prog...
By Qi Zhang, Heajun An, Prakriti Dumaru, Sang Won Lee, Lifu Huang, Pamela J. Wisniewski, Jin-Hee Cho
arXiv:2608.21829v1 Announce Type: cross
Abstract: Retrieval-augmented generation treats the document store as a frozen input, and the systems that instead let an agent curate one never measure what c...
By Yu Pan, Hongfeng Yu
arXiv:2608.22672v1 Announce Type: new
Abstract: Energy system operation contains a loop of work that automation has never taken over: posing the optimization problem the current cycle should solve, d...
By Xiaoyu Zhang, Qiuye Sun, Jiachen Xu, Zhongming Yao, Yushuai Li
arXiv:2608.22697v1 Announce Type: new
Abstract: Search rankings are valuable because human attention is scarce and sequential. Higher-placed alternatives are easier to find, so they are examined and...
By Davood Wadi, Yu Ma
arXiv:2608.21946v1 Announce Type: cross
Abstract: Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable exp...
By Can Xie, Yuyi Zhou, Wen Yang, Ziyi zhang, Siyao Song, Yingzhuo Deng, Shuo Ren, Jiajun Zhang