arXiv:2608. 10526v1 Announce Type: cross Abstract: Motivated by decentralized applications, we study cooperative multi-agent bandits in continuous (Lipschitz) action spaces when the Lipschitz constant is unknown.
By Ricardo Parada, Chenzhang Zhao, William Chang
arXiv:2608. 10363v1 Announce Type: new Abstract: AI agents can accelerate nutrition research, but their analyses inherit the identity, semantic, and release ambiguities of the underlying data.
By Lin Liao, Peng Li
arXiv:2608. 11095v1 Announce Type: new Abstract: Agentic coding READMEs like CLAUDE.
By Kushal Chakrabarti
arXiv:2608. 09934v1 Announce Type: cross Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors.
By Vitalii Belov, Artyom Sosedka, Andrey Sakhovskiy, Elizaveta Kovtun, Artyom Boyarskikh, Semen Budennyy
arXiv:2605. 15850v3 Announce Type: replace-cross Abstract: In recent years, generative AI (GenAI) in educational settings has become ubiquitous in university students' daily lives, despite its potential to induce over-reliance, metacognitive disengagement, and diminished learning when used unrestrictedly.
By Janne Rotter, Pau Benazet i Montobbio, Davinia Hern\'andez-Leo
arXiv:2608. 10664v1 Announce Type: new Abstract: The Relativity of Causal Knowledge (RCK) explains how a network of agents with different structural causal models can exchange causal knowledge through a shared interventionally consistent abstraction, or backbone.
By Fabrizio Russo, Mark Somers
arXiv:2608. 10157v1 Announce Type: new Abstract: Self-improving agents seek to reduce the human engineering effort behind AI systems by enabling them to evolve and self-improve their performance over time.
By Vivek Kulkarni, Sudipta Paul, Aounon Kumar, Nicholas Tzou, Srinivas Chappidi
arXiv:2608. 09944v1 Announce Type: cross Abstract: Modern web interfaces are increasingly difficult to use with screen readers, particularly when pages update dynamically or hide important structure behind visual layout.
By Santosh Patapati
arXiv:2608. 10042v1 Announce Type: cross Abstract: Tool-use LLMs are increasingly asked to act on users' behalf, but existing benchmarks usually focus on profile recall, style imitation, generic tool use, or response-level personalization.
By Xuexiong Yin, Zechuan Chen, Yongsen Zheng, Yuxiang Zhang, Jingyuan Yang, Bin Wang, Yubin Wang, Keze Wang
arXiv:2608. 10601v1 Announce Type: cross Abstract: Two instruments of EU digital law place inference at their centre and mean different things by it.
By Nicola Fabiano
arXiv:2608. 10715v1 Announce Type: cross Abstract: Over the past several years, LLM-powered chatbots and agents have become widely used as a tool for academic writing.
By Lena Holzwarth, Rita Gonz\'alez-M\'arquez, Dmitry Kobak
arXiv:2608. 10494v1 Announce Type: new Abstract: Earth observation (EO) agents construct scientifically valid tool workflows and ground their conclusions in current geospatial evidence.
By Xin Xiao, Jiang Zhong, Junnan Zhu, Yingchao Feng, Peijin Wang, Yidan Zhang, Kaiwen Wei
arXiv:2501. 11655v3 Announce Type: replace-cross Abstract: This paper proposes a novel learning approach for designing Kazantzis-Kravaris or nonlinear Luenberger (KKL) observers for autonomous nonlinear systems.
By M. Umar B. Niazi, John Cao, Matthieu Barreau, Karl Henrik Johansson
arXiv:2608. 10424v1 Announce Type: new Abstract: A slew of recent works develop agents for solving research problems end-to-end, a paradigm increasingly referred to as autoresearch.
By Au Kwok Chun, Abhigyan Acherjee, Amrutha Rao, Zaiqian Chen, Kazem Meidani, C. Bayan Bruss, Micah Goldblum
arXiv:2608. 10444v1 Announce Type: cross Abstract: Large language models (LLMs) have made substantial progress on reasoning tasks that require increasingly long and complex inferential chains.
By Si'an Xie (Beijing University of Posts and Telecommunications), Jiaxun Liu (Peking University), Biao Yang (Kuaishou Technology), Wei Yuan (Kuaishou Technology), Fan Yang (Kuaishou Technology), Tingting Gao (Kuaishou Technology), Ming Wu (Beijing University of Posts and Telecommunications)
arXiv:2608. 10108v1 Announce Type: new Abstract: Long-horizon agents accumulate trajectories spanning hundreds of interleaved reasoning, action, and observation steps, where answering a query may depend on evidence buried far back in the history.
By Beidi Zhao, Yaoqi Chen, Yuru Feng, Menghao Li, Qianxi Zhang, Baotong Lu, Jianan Lu, Zhirui Wang, Xinjiang Wang, Shusen Xu, Zengzhong Li, Xiaoxiao Li, Qi Chen
arXiv:2608. 10628v1 Announce Type: cross Abstract: Long-document understanding often requires reasoning over many visually rich pages, making inference costly and prone to context rot.
By Kaican Li, Weiyan Xie, Lewei Yao, Jiannan Wu, Lanqing Hong, Yongxiang Huang, Nevin L. Zhang
arXiv:2608. 10402v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language models is moving toward multi-turn agentic workloads, where rollout tasks repeatedly pause for external environments, resume with growing contexts, and finish at highly variable times.
By Yanyu Ren, Xizheng Wang, Xiao Liu, Bowen Lv, Hanchen Zhang, Shudan Zhang, Hanyu Lai, Shuai Wang, Li Chen, Dan Li, Jie Tang
arXiv:2608. 10366v1 Announce Type: new Abstract: Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coordinated use of tools such as notebooks, IDEs, terminals, browsers, and databases within real operating environments.
By Mizanur Rahman, Mohammed Saidul Islam, Ridwan Mahbub, Md Tahmid Rahman Laskar, Shafiq Joty, Enamul Hoque Prince
arXiv:2608. 09959v1 Announce Type: cross Abstract: AI weather models are in the process of revolutionising weather forecasting.
By Anna Allen, Wessel P. Bruinsma, Michael Maier-Gerber, Harrison Cook, Matthew Chantry, Richard E. Turner