Multi-Agent LLMs

LLM: Large Language Model

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22 papers in the last four weeks, up 144% on the four weeks before. 0.2% of all new papers.

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Latest papers 212

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Mechanism Design Is Not Enough: Prosocial Agents for Cooperative AI
May 8, 2026Xuanqiang Angelo Huang, Charlie Tharas, Samuele Marro +4Mechanism Design AI Agent Safety
ETH Zürich · University of Oxford · Institute for Decentralized AI +5
SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model
May 8, 2026Shiyue Cao, Pei Xu, Likun Yang +3Opponent Modeling Multi-Agent Reasoning
School of Artificial Intelligence, University of Chinese Academy of Sciences & Institute of Automation, Chinese Academy of Sciences Beijing, China · National Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences Beijing, China +1
Verifier-Backed Hard Problem Generation for Mathematical Reasoning
May 7, 2026Yuhang Lai, Jiazhan Feng, Yee Whye Teh +1Reinforcement Learning with Verifiable Rewards Multi-Agent LLMs
Department of Data Science, City University of Hong Kong · School of Intelligence Science and Technology, Peking University · Work done during Jiazhan’s visiting at the Department of Statistics, University of Oxford. +2
Improving the Efficiency of Language Agent Teams with Adaptive Task Graphs
May 7, 2026Elizabeth Mieczkowski, Alexander Ku, Tiwalayo Eisape +5Multi-Agent Coordination LLM Agent Orchestration
Princeton University · University of Cambridge · MIT +1
Agent Island: A Saturation- and Contamination-Resistant Benchmark from Multiagent Games
May 5, 2026Connacher MurphyGame-Playing Agents Benchmark Design
Stanford University
CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verification
May 5, 2026Severin Ye, Xiao Kong, Xiaopeng He +2Healthcare Hallucination Detection
School of Computer Science and Engineering Kyungpook National University Daegu, Republic of Korea · School of Airspace Science and Engineering Shandong University Weihai, China · Department of English Language and Literature, Kyungpook National University, Daegu, Republic of Korea
Mitigating Misalignment Contagion by Steering with Implicit Traits
May 4, 2026Maria Chang, Ronny Luss, Miao Liu +3LLM Alignment Language Model Steering
IBM Research Yorktown Heights, NY 10598, USA
Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation
May 3, 2026Yiheng Yao, Chelsea Zou, Robert D. HawkinsMulti-Agent Coordination Multi-Agent Negotiation
Stanford University
6G Needs Agents: Toward Agentic AI-Native Networks for Autonomous Intelligence
May 2, 2026Mohamed Amine Ferrag, Abderrahmane Lakas, Merouane Debbah6G Networks LLM Agent Orchestration
Department of Computer and Network Engineering, United Arab Emirates University, UAE · Research Institute for Digital Future, Khalifa University, UAE
Who Decides What Is Harmful? Content Moderation Policy Through A Multi-Agent Personalised Inference Framework
May 2, 2026Ewelina Gajewska, Michal Wawer, Katarzyna Budzynska +1LLM Guardrails Content Moderation
Warsaw University of Technology, Warsaw, Poland
TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
May 1, 2026Yi Xie, Siao Liu, Falong Fan +3Multi-Agent System Optimization Multi-Agent Coordination
Department of Electrical & Computer Engineering, University of Arizona · Future Science and Engineering College, Soochow University · INSAIT, Sofia University ”St. Kliment Ohridski” +1
Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment
May 1, 2026Tanav Singh Bajaj, Nikhil Singh, Karan Anand +1Opinion Dynamics AI Agent Safety
Department of Computer Science, University of British Columbia, Vancouver, Canada · Department of Artificial Intelligence, IIT Hyderabad, Hyderabad, India · Amazon, Delhi, India.
When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems
May 1, 2026Lingxi Zhang, Guangtao Zheng, Hanjie ChenAdversarial Attacks Language Model Robustness
1Rice University · University of Virginia
AgenticAITA: A Proof-Of-Concept About Deliberative Multi-Agent Reasoning for Autonomous Trading Systems
May 1, 2026Ivan LetteriMulti-Agent Orchestration AI Agent Safety
Department of Information Engineering, Computer Science, and Mathematics, Center of Excellence for Research DEWS, University of L’Aquila, Via Vetoio, Coppito, 67100 L’Aquila, Italy
Scaling Video Understanding via Compact Latent Multi-Agent Collaboration
May 1, 2026Kerui Chen, Jinglu Wang, Jianrong Zhang +3Multi-Agent Collaboration Long-Video Understanding
Microsoft Research Asia · Zhejiang University · Guanming Lab.
What Suppresses Nash Equilibrium Play in Large Language Models? Mechanistic Evidence and Causal Control
Apr 29, 2026Paraskevas V. Lekeas, Giorgos StamatopoulosNash Equilibrium Game Theory
DreamWorks Animation, Glendale, USA · Department of Economics, University of Crete2026 Rethymno, Crete, Greece
Think it, Run it: Autonomous ML pipeline generation via self-healing multi-agent AI
Apr 29, 2026Adela Bara, Gabriela Dobrita, Simona-Vasilica OpreaAutomated Machine Learning Multi-Agent LLMs
Bucharest University of Economic Studies, Department of Economic Informatics and Cybernetics, no.6 Piața Romană, Bucharest, 010374, Romania
From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling
Apr 28, 2026Jianghao Lin, Zi Ling, Chenyu Zhou +4Multi-Agent Debate Multi-Agent LLMs
Antai College of Economics and Management, Shanghai Jiao Tong University · University of Chicago Booth School of Business · School of Economics and Management, Tsinghua University +1
Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest
Apr 28, 2026Abigail O'Neill, Alan Zhu, Mihran Miroyan +2Multi-Agent Coordination Multi-Agent Negotiation
University of California, Berkeley
RefEvo: Agentic Design with Co-Evolutionary Verification for Agile Reference Model Generation
Apr 27, 2026Yifan Zhang, Jianmin Ye, Jiahao Yang +1Electronic Design Automation LLM-Based Program Synthesis
School of Integrated Circuits, Southeast University, China · National Center of Technology Innovation for EDA, China
Strategic Bidding in 6G Spectrum Auctions with Large Language Models
Apr 27, 2026Ismail Lotfi, Ali GhrayebMechanism Design Wireless Resource Allocation
College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making
Apr 26, 2026Zhuohui Zhang, Bin Cheng, Bin HeSequential MARL Offline RL
Department of Control Science and Engineering, Tongji University, Shanghai 201804, China · Shanghai Institute of Intelligent Science and Technology; Shanghai Research Institute for Intelligent Autonomous Systems; State Key Laboratory of Autonomous Intelligent Unmanned Systems, Shanghai 200120, China
ArgRE: Formal Argumentation for Conflict Resolution in Multi-Agent Requirements Negotiation
Apr 25, 2026Haowei Cheng, Milhan Kim, Chong Liu +6Requirements Engineering Multi-Agent Negotiation
Department of Computer Science and Communications Engineering, Waseda University, Tokyo, Japan · College of Architecture and Urban Planning, Tongji University, Shanghai, China · Advanced Institute of So-Go-Chi (Convergence Knowledge) Informatics, Tohoku University, Miyagi, Japan +1
Peer Identity Bias in Multi-Agent LLM Evaluation: An Empirical Study Using the TRUST Democratic Discourse Analysis Pipeline
Apr 24, 2026Juergen DietrichLLM Sycophancy Language Model Bias Evaluation
TRUST Project — democracy-intelligence.de
Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems
Apr 23, 2026Ye Yu, Heming Liu, Haibo Jin +3Multi-Agent System Optimization LLM Agent Training
University of Illinois Urbana-Champaign, IL, USA
ActuBench: A Multi-Agent LLM Pipeline for Generation and Evaluation of Actuarial Reasoning Tasks
Apr 22, 2026Jan-Philipp SchmidtLLM Evaluation Educational Assessment
TH Köln, Institut für Versicherungswesen (ivwKöln)
Memory-Augmented LLM-based Multi-Agent System for Automated Feature Generation on Tabular Data
Apr 22, 2026Fengxian Dong, Zhi Zheng, Xiao Han +5Tabular ML Multi-Agent LLMs
University of Science and Technology of China · Zhejiang University of Technology · Meituan
Information Aggregation with AI Agents
Apr 21, 2026Spyros GalanisAI Agent Evaluation Multi-Agent Reasoning
Department of Economics, University of Durham
TEAM-SimHRA: A Team-Based Simulation Framework for Human Reliability Analysis Using Multi-Agent Large Language Models
Apr 21, 2026Xingyu Xiao, Jiejuan Tong, Jingang Liang +1Human Behavior Simulation Agent-Based Modeling
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, China · National Key Laboratory of Human Factors Engineering, Beijing, 100094, China
Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures
Apr 20, 2026Zixiang Wang, Mengjia Gong, Qiyu Sun +5Multi-Agent Coordination Multi-Agent Systems
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China · School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China · School of Electrical Engineering and Automation, Nantong University, Nantong 226019, China +2

May 8, 2026, cs.GTJ/K move · Enter open · S save

Mechanism Design Is Not Enough: Prosocial Agents for Cooperative AI

Xuanqiang Angelo Huang, Charlie Tharas, Samuele Marro, Van Q. Truong+3

ETH Zürich · University of Oxford · Institute for Decentralized AI+5

Mechanism Design AI Agent Safety Multi-Agent LLMs

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Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI safety. While mechanism design, as the theory of designing rules to align individual and collective objectives, can incentivize cooperative behavior, it is still an open question whether it alone is sufficient to maximize LLM agents' social welfare. This work proves that the answer is negative: drawing from incomplete contract theory, we formally show that when contracts cannot distinguish all relevant future contingencies, there is a strictly positive welfare loss that no realistic mechanism can eliminate. We show that prosocial agents, who weigh others' welfare alongside their own, can close this gap and achieve outcomes that are socially superior and individually beneficial. Experimentally, we show that in multi-agent resource-allocation environments and canonical social dilemmas where agents are powered by large language models, prosociality is beneficial. The implication for AI safety is clear: to enable cooperative interactions at scale, designing adequate mechanisms is not sufficient; agents must be built to be intrinsically prosocial.

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