NEURIPS 2025 "multi-agent systems" Papers
16 papers found
AgentBreeder: Mitigating the AI Safety Risks of Multi-Agent Scaffolds via Self-Improvement
J Rosser, Jakob Foerster
NEURIPS 2025spotlightarXiv:2502.00757
4
citations
Automated Composition of Agents: A Knapsack Approach for Agentic Component Selection
Michelle Yuan, Khushbu Pahwa, Shuaichen Chang et al.
NEURIPS 2025posterarXiv:2510.16499
Belief-Calibrated Multi-Agent Consensus Seeking for Complex NLP Tasks
Wentao Deng, Jiahuan Pei, Zhiwei Xu et al.
NEURIPS 2025posterarXiv:2510.06307
HYPRL: Reinforcement Learning of Control Policies for Hyperproperties
Tzu-Han Hsu, Arshia Rafieioskouei, Borzoo Bonakdarpour
NEURIPS 2025posterarXiv:2504.04675
2
citations
Knowledge Starts with Practice: Knowledge-Aware Exercise Generative Recommendation with Adaptive Multi-Agent Cooperation
Yangtao Zhou, Hua Chu, chen et al.
NEURIPS 2025poster
KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systems
Hancheng Ye, Zhengqi Gao, Mingyuan Ma et al.
NEURIPS 2025posterarXiv:2510.12872
1
citations
Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve
Yuanzhe Liu, Ryan Deng, Tim Kaler et al.
NEURIPS 2025posterarXiv:2505.23946
Many LLMs Are More Utilitarian Than One
Anita Keshmirian, Razan Baltaji, Babak Hemmatian et al.
NEURIPS 2025oralarXiv:2507.00814
2
citations
MetaMind: Modeling Human Social Thoughts with Metacognitive Multi-Agent Systems
Xuanming Zhang, Yuxuan Chen, Samuel (Min-Hsuan) Yeh et al.
NEURIPS 2025oralarXiv:2505.18943
6
citations
MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
Haoyang Fang, Boran Han, Nick Erickson et al.
NEURIPS 2025posterarXiv:2505.13941
7
citations
MURKA: Multi-Reward Reinforcement Learning with Knowledge Alignment for Optimization Tasks
WANTONG XIE, Yi-Xiang Hu, Jieyang Xu et al.
NEURIPS 2025poster
Rainbow Delay Compensation: A Multi-Agent Reinforcement Learning Framework for Mitigating Observation Delays
Songchen Fu, Siang Chen, Shaojing Zhao et al.
NEURIPS 2025poster
SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning
Wanjia Zhao, Mert Yuksekgonul, Shirley Wu et al.
NEURIPS 2025posterarXiv:2502.04780
18
citations
Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
Lorenzo Magnino, Kai Shao, Zida Wu et al.
NEURIPS 2025posterarXiv:2510.22158
2
citations
Towards Doctor-Like Reasoning: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients
Yuxing Lu, Gecheng Fu, Wei Wu et al.
NEURIPS 2025poster
6
citations
Towards Principled Unsupervised Multi-Agent Reinforcement Learning
Riccardo Zamboni, Mirco Mutti, Marcello Restelli
NEURIPS 2025posterarXiv:2502.08365
2
citations