AI agents

Tool use, function calling, orchestration and the protocols that let models act rather than only answer.

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arXiv AI
Jul 1

What Probing Reveals about Autonomous Driving: Linking Internal Prediction Errors to Ego Planning

arXiv:2606. 31106v1 Announce Type: cross Abstract: Large-scale datasets and fast simulators have enabled improvements in driving policies that appear safe and robust, yet strong performance in nominal scenarios can still mask flawed reasoning and unsafe heuristics.

By Hyeonchang Jeon, Kyungbeom Kim, Eugene Vinitsky, Kyung-Joong Kim
arXiv AI
Jul 1

FinPersona-Bench: A Benchmark for Longitudinal Psychometric Stability of Autonomous Financial Agents

arXiv:2606. 31522v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous financial agents initialized with explicit behavioral mandates such as "preserve capital" or "avoid speculative bets" that are meant to govern every decision throughout deployment.

By Muhammad Usman Safder (Steve), Ayesha Gull (Steve), Rania Elbadry (Steve), Fan Zhang (Steve), Yankai Chen (Steve), Xueqing Peng (Steve), Xue (Steve), Liu, Preslav Nakov, Zhuohan Xie
arXiv AI
Jul 1

What Drives Interactive Improvement from Feedback?

arXiv:2606. 30774v1 Announce Type: new Abstract: We study when natural-language feedback produces improvement beyond the gains obtainable from repeated attempts alone.

By Bart{\l}omiej Cupia{\l}, Jan {\L}ojek, Miko{\l}aj Garstecki, Szymon Pob{\l}ocki, Alicja Ziarko, Piotr Mi{\l}o\'s
arXiv AI
Jul 1

LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents

arXiv:2606. 31045v1 Announce Type: new Abstract: Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory environments remains challenging.

By Jingpu Yang, Fengxian Ji, Zhengzhao Lai, Zhexuan Cui, Guangxian Ouyang, Qian Jiang, Fan Zhang, Min Peng, Qianqian Xie, Preslav Nakov, Zhuohan Xie
arXiv AI
Jul 1

Think in English, Answer in Korean: Efficient Adaptation of Multilingual Tool-Using Agents

arXiv:2606. 31648v1 Announce Type: new Abstract: We present LuckyStar 111B, a 111B-parameter hybrid reasoning model developed through a collaboration between Cohere and LG CNS for Korean-English enterprise agents under practical memory and serving constraints.

By Utsav Garg, Sungjin Hong, Jason Jung, Justin Lee, Shaan Desai, Joon Hee Kim, Anirudh Shrinivason, Edmond Wen, Susie Park
arXiv AI
Jul 1

A Self-Evolving Agentic System for Automated Generation and Execution of Biological Protocols

arXiv:2606. 31763v1 Announce Type: new Abstract: Autonomous wet-lab experimentation requires more than plausible protocol text: biological intent, quantitative procedures, device constraints and experimental feedback must remain aligned from protocol and SOP design to code and physical execution.

By Yankai Jiang, Weiting Tang, Haoran Sun, Zhenyu Tang, Yuejie Hou, Yingnan Han, Rubo Wang, Yueyuxiao Yang, Cheng Liang, Lilong Wang, Wenjie Lou, Xiaosong Wang, Lei Bai, Meng Yang
arXiv AI
Jul 1

Contrastive Reflection for Iterative Prompt Optimization

arXiv:2606. 30840v1 Announce Type: new Abstract: LLM agents are becoming central to information retrieval: they issue retrieval queries, synthesize answers, and increasingly serve as judges for IR evaluation.

By Derek Koh, Jinghui Mo, Benjamin H. Le, Jiening Zhan, Baofen Zheng, Kevin Bevis, Nathaniel C. Owen, Lauren Elizabeth Charney, Wenqiong Liu, Jingwei Wu
arXiv AI
Jul 1

Who Determines the Meaning of an Emotion? Affective Sovereignty as an Epistemic Consequence of Measurement Limits

arXiv:2606. 31442v1 Announce Type: new Abstract: Emotion-sensing AI is rapidly becoming embedded in vehicles, home appliances, dialogue agents, and social infrastructure, giving rise to a sphere in which emotion is no longer confined to individual experience but is instead observed and computed at a societal scale, a domain we term the Affectosphere.

By Keito Inoshita