arXiv:2607. 25415v1 Announce Type: new Abstract: Production LLM agents are increasingly assembled from a frozen model wrapped in a harness: a prompt template, a tool set, a memory/retrieval layer, a planning strategy, and a verification policy.
By Debjyoti Paul
arXiv:2607. 25400v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly entrusted with natural-language workflow instructions (e.
By Jincheng Wang, Min Zheng, Tao Wei
arXiv:2607. 25446v1 Announce Type: new Abstract: Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), how members align (coordination), and which algorithm fuses their work (collaboration protocol).
By Huan Chen, Xiang Song, Jian Jin, Pan Ren, Liang-Jie Zhang
arXiv:2607. 25560v1 Announce Type: new Abstract: Agent skills package reusable procedures that improve downstream performance.
By Jianing Geng, Ruiqi He, Zekun Fei, Biao Yi, Ruijie Wang, Zheli Liu, Xia Hu, Xuansheng Wu, Qingkai Zeng
arXiv:2605. 05811v2 Announce Type: replace Abstract: Workbook-scale spreadsheet understanding is increasingly important for language-model-based data analysis agents, but remains challenging because relevant information is often distributed across multiple sheets with heterogeneous schemas, layouts, and implicit relationships.
By Yiming Lei, Yuhang Yao, Yujia Zhang, Yiqi Wang, Bo Guan, Depei Zhu, Chunhui Wang, Zhuonan Hao, Tianyu Shi
arXiv:2605. 05580v2 Announce Type: replace Abstract: Quantitative trading agents have demonstrated substantial promise in automating factor discovery, signal aggregation, and portfolio execution.
By Yishuo Yuan, Jiayi Sheng, Sirui Zeng, Jiaqi Wang, Jiaheng Liu
arXiv:2607. 24779v1 Announce Type: new Abstract: Online advertising bidding systems typically deploy multiple offline-trained expert models (e.
By Ji Wu, Yunshan Peng, Wentao Bai, Yunke Bai, Wenzheng Shu, Jinan Pang, Yanxiang Zeng, Xialong Liu
arXiv:2607. 25728v1 Announce Type: cross Abstract: This paper presents a cooperative indoor UAV guidance framework that combines a shared voxel-map world model with a multi-agent Soft Actor-Critic (MASAC) controller.
By Thomas Hickling, Dylan Wynne, Yu Su, Nabil Aouf
arXiv:2607. 24770v1 Announce Type: new Abstract: Procedural tasks such as furniture assembly and home repair impose substantial cognitive demands because users must interpret instructions, track task progress, reason about spatial state, and recover from errors while performing physical actions.
By Azizul Zahid, Subrata Biswas, Bashima Islam, Sai Swaminathan
arXiv:2607. 25108v1 Announce Type: cross Abstract: Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, protocols, and patient populations.
By Zihan Li, Feiyang Liu, Dandan Shan, Ruibo Wang, Qingqi Hong
arXiv:2607. 25253v1 Announce Type: new Abstract: Online recommendation has traditionally taken place after a user enters a platform, which determines the candidate pool and the ranking shown to the user.
By Deyao Hong, Kehan Zheng, Qian Li, Jun Zhang, Jie Jiang, Hongning Wang
arXiv:2607. 25032v1 Announce Type: cross Abstract: Agent Skills are an emerging way to extend large language model agents with reusable procedural knowledge that the agent loads on demand.
By Giuseppe Destefanis
arXiv:2607. 24772v1 Announce Type: new Abstract: Geoscience research requires complex analysis and domain expertise, with remote sensing (RS) observations as a key foundation.
By Bingxian Wu, Yu Zhang, Zonghao Guo, Tang Liu, Chen Qian, Yuxiang Lu, Xingbo Du, Yanghao Li, Yidan Zhang, Chi Chen, Ling Yao, Maosong Sun
arXiv:2607. 26005v1 Announce Type: cross Abstract: Self-play in simulation produces robust driving policies at scale.
By Yuan Yin, Elias Ramzi, Marc Lafon, Valentin Charraut, Victor Bares, Yihong Xu, \'Eloi Zablocki, Alexandre Boulch, Thibault Buhet, Andrei Bursuc, Matthieu Cord
arXiv:2605. 30880v4 Announce Type: replace-cross Abstract: World models for interactive text agents must typically be learned from observation-action trajectories alone.
By Jiaxin Bai, Yue Guo, Yifei Dong, Jiaxuan Xiong, Tianshi Zheng, Yixia Li, Tianqing Fang, Yufei Li, Yisen Gao, Haoyu Huang, Zhongwei Xie, Hong Ting Tsang, Zihao Wang, Lihui Liu, Jeff Z. Pan, Yangqiu Song
arXiv:2607. 25152v1 Announce Type: new Abstract: Long-running autonomous agents plan, act, and judge their own completion without human intervention.
By Hyundoo Park, Byungho Choi
arXiv:2604. 07126v2 Announce Type: replace-cross Abstract: Predicting vehicle trajectories plays an important role in autonomous driving, transportation safety analysis, traffic operations, etc.
By Diyi Liu, Zihan Niu, Tu Xu, Xingchen Zhang, Lishan Sun
arXiv:2607. 25570v1 Announce Type: cross Abstract: The development of autonomous vehicles (AVs) usually relies heavily on data-driven artificial intelligence (AI) models that require large volumes of sensor data with ground-truth annotations.
By A. Contreras, D. Porres, R. Abad, P. Cano, G. Villalonga, A. M. L\'opez, A. Hern\'andez-Sabat\'e
arXiv:2607. 26041v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly act through desktop GUIs to complete long-horizon tasks.
By Abhishek Pillai, Samir Kumar Nayak, Yuan Chen
arXiv:2607. 25140v1 Announce Type: new Abstract: This paper studies the behavior of language models in a multi-agent crowd simulation, focusing on how affect propagates among agents that perceive and appraise one another.
By Funda Durupinar