Multi-Agent LLM Systems

LLM: Large Language Model

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85 papers in the last four weeks, up 107% on the four weeks before. 0.8% of all new papers.

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ChatT2: An Adaptive Framework for Developing a Large Language Model-Based Agent for Natural Product Domain Research
Sep 22, 2026Yihan Wang, Qiandi Gao, Yihui Zhuang +4Multi-Agent LLM Systems AI-Assisted Scientific Research
Center for Biological Science and Technology, Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, Guangdong, 519087, China.
A Task-Oriented Multi-Agent Framework for Complex Wearable Health Analysis
Sep 21, 2026Kunpeng YangMulti-Agent LLM Systems LLM Agent Orchestration
Renmin University of China
Language-model groups overstate consensus when replaying human deliberation on a reasoning task
Sep 17, 2026Tengfei ShaoMulti-Agent LLM Systems LLM Agent Evaluation
Global Education Center, Waseda University, Tokyo, Japan
MaSCoD: A Multi-Agent Framework for Structural-Context-Guided Candidate Causal Graph Generation
Sep 17, 2026Yudai Nakada, Yuichiro Nishiura, Jin Michael SplichalMulti-Agent LLM Systems Causal Discovery
SCSK Corporation Tokyo, Japan
Contagion on the Trading Floor: How Adversarial Signals Spread in Multi-Agent Trading Systems
Sep 17, 2026Qi Rong Sua, Junhao Dong, Nguyen Duc Thai +3Multi-Agent LLM Systems Adversarial Robustness of Language Models
Nanyang Technological University, Singapore · Centre for Frontier AI Research, IHPC, A*STAR, Singapore · National University of Singapore, Singapore
MAGS: Multi-agent Auto-formalization Guarantees Safety for Agentic Outputs
Sep 16, 2026Albert Wu, Nicholas Roberts, Tzu-Heng Huang +5Multi-Agent LLM Systems Formal Verification
University of Wisconsin-Madison · Princeton University
Clueing up LLMs with Tool-Augmented Deductive Reasoning
Sep 16, 2026Rebecca Ansell, Autumn Toney-WailsMulti-Agent LLM Systems AI Agent Benchmarks
Georgetown University · Syntheos, Corp · UNU-MERIT
Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery
Sep 16, 2026Xiangfan Wu, Zonghao Ying, Huiyu Wu +4Multi-Agent LLM Systems AI Agent Safety
Tencent Zhuque Lab
DualSQL: Text-to-SQL with Multi-Agent Reinforcement Learning
Sep 16, 2026Shijie Chen, Yu Gan, Yeounoh Chung +6Multi-Agent LLM Systems Text-to-SQL
The Ohio State University · Google LLC
Verifiable Social Reasoning for LLM Assistants
Sep 15, 2026Amir Taubenfeld, Zorik Gekhman, Avigail Grinstein-Dabush +6Multi-Agent LLM Systems Theory of Mind
Google Research · Hebrew University · University of Cambridge
Emergence World: Adversarial Stress-Testing of Long-Horizon Multi-Agent Systems
Sep 15, 2026Deepak Akkil, Tamer Abuelsaad, Karthik Vikram +5Multi-Agent LLM Systems Long-Horizon Agent Evaluation
Emergence AI
Mo' Models, Mo' Problems: How to best select model pools when designing Multi-Agent Systems
Sep 15, 2026Sara Vera Marjanović, Jiacheng Xu, Aleksandr Laptev +3Model Selection Multi-Agent LLM Systems
University of Copenhagen · Work done during internship at NVIDIA · NVIDIA
Interactive Memory Learning for Long-Term Conversations
Sep 15, 2026Cai Ke, Jiangyue Yan, Han Zhang +5Multi-Agent LLM Systems Long-Term Conversational Memory
Harbin Institute of Technology, Shenzhen, China · Pengcheng Laboratory, China
HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses
Sep 14, 2026Jieyuan Liu, Mengzhou Hu, Jefferson Chen +10Multi-Agent LLM Systems Scientific Hypothesis Generation
University of California San Diego · 2Texas A&M University · 3Carnegie Mellon University +1
Assembling the CREW: A Collaborative Multi-agent Reinforcement Learning Framework for Automated Related Work Generation
Sep 14, 2026Hai-Dang Dang, Bao-Yen Pham, Bao Nguyen +2Multi-Agent LLM Systems RL for LLM Agents
Hanoi University of Science and Technology · The Chinese University of Hong Kong · Hanoi University of Industry
RSIAgent: Autonomous Exploration for Recursive Self-improvement in New Environments
Sep 14, 2026Sibo Zhu, Shicheng Fan, Xinyue Wang +3Multi-Agent LLM Systems LLM Agent Self-Improvement
Aether AI · University of California San Diego · ‡Work done during internship in Aether AI +1
EMR: Self-Evolving Medical Multi-Agent System via Experience Mining and Reuse
Sep 14, 2026Dongsheng Shi, Yue Li, Xin Yi +1Continual Learning for LLM Agents Multi-Agent LLM Systems
East China Normal University · City University of Hong Kong
Translating the Translator: Decomposing the Cost of English-Forced Inter-Agent Communication
Sep 14, 2026Kushagra Agrawal, Yuming Feng, Man-Fai LeungMultilingual Language Models Multilingual Language Model Evaluation
Faculty of Science and Engineering Åbo Akademi University Turku, Finland · School of Computer Science and Engineering Chongqing Sanxia University of Science and Technology Chongqing, China · School of Computing and Information Science Faculty of Science and Engineering Anglia Ruskin University Cambridge, UK
BusMA: A Bus Communication Substrate for Multi-Agent Systems
Sep 14, 2026Yanwen Peng, Delvin Ce Zhang, Xi Wang +1Multi-Agent LLM Systems Multi-Agent Coordination
Department of Computer Science, The University of Sheffield, Sheffield, United Kingdom
CoMem: Collective-Individual Memory Synergy for Evolutionary Multi-Agent Systems
Sep 14, 2026Chengxin Yu, Zhaoxin Fan, Faguo Wu +3Multi-Agent LLM Systems Multi-Agent Collaboration
Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, School of Artificial Intelligence, Beihang University · Beijing academy of blockchain and edge computing · National University of Defense Technology +1
NDT Factory: Synthesizing Verified Network Digital Twins from Semantic Models via Multi-Agent LLM
Sep 14, 2026Sudipta Acharya, Petar Djukic, Burak KantarciMulti-Agent LLM Systems LLM-Based Program Synthesis
University of Ottawa, Ottawa, ON, Canada · Bell Labs Research, 600 March Road, Kanata, ON K2K 2E6, Canada
AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems
Sep 14, 2026Zachary Johnson, Nigel Boachie Kumankumah, Somya Chatterjee +8Multi-Agent LLM Systems Privacy-Preserving Language Models
Microsoft
Loop-Back Authority in LLM Agent Teams: A Paired Experiment on Flat and Hierarchical Coordination
Sep 13, 2026Burak Agachan, Max van Duijn, Amirhossein ZohrehvandMulti-Agent LLM Systems Multi-Agent Coordination
Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Leiden, The Netherlands
Disentangling Topology and Diversity in Multi-Agent LLMs for Multilingual Low-Resource Emotion Detection
Sep 13, 2026Ulugbek Shernazarov, Charitha Ruwansiri Weerakon Basnayake, Abdelkhaleq El Jarjini +2Multi-Agent LLM Systems Emotion Recognition
Télécom SudParis, Institut Polytechnique de Paris, Évry-Courcouronnes, France · Cardiff Metropolitan University, Cardiff, United Kingdom · Aberystwyth University, Aberystwyth, United Kingdom
How AI Coders Discuss, Disagree, and Reach Consensus: Challenges and Opportunities for LLM-Based Qualitative Coding
Sep 12, 2026Jeongyeon Kim, John MitchellMulti-Agent LLM Systems LLM Agent Evaluation
Stanford University, Stanford, CA, USA
Agentic Share-of-Search: A Multi-Agent AI System for Competitive Decision-Making in LLM-Mediated E-Commerce
Sep 12, 2026Spandan Ghose ChowdhuryMulti-Agent LLM Systems AI-Assisted Decision Making
College of Computing, Georgia Institute of Technology Atlanta, Georgia, USA
When Agents Disagree: Bayesian Backward Reasoning as a Label-Free Anchor for Multi-Agent Collective Decision-Making
Sep 12, 2026Ken Chen, Wei Wang, Sachith Seneviratne +2Multi-Agent LLM Systems Bayesian Inference
Department of Mechanical Engineering, The University of Melbourne, Melbourne, Australia · Department of Mechanical Engineering, Sri Lanka Institute of Information Technology, Sri Lanka
But How Would AI Agents Run a Town's Economy?
Sep 11, 2026Sajal Regmi, Siddhartha Pudasaini, Chetan Phakami PunMulti-Agent LLM Systems Human Behavior Simulation
Karela Technologies Inc. USA
Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization
Sep 11, 2026Dong-Jae Koh, Huisu Kim, SeongHwan Yoon +4Multi-Agent LLM Systems LLM Reliability
School of Computer Science and Engineering, Kyungpook National University, South Korea
Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs
Sep 9, 2026Kostia Kudriavtsev, Parvez Rafi, Sha SundaramMulti-Agent LLM Systems
Apple Seattle, WA and Cupertino, CA, USA

Sep 22, 2026, cs.AIJ/K move · Enter open · S save

ChatT2: An Adaptive Framework for Developing a Large Language Model-Based Agent for Natural Product Domain Research

Yihan Wang, Qiandi Gao, Yihui Zhuang, Liangjun Ge+3

Center for Biological Science and Technology, Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, Guangdong, 519087, China.

Multi-Agent LLM Systems AI-Assisted Scientific Research Agentic RAG

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Scientific investigations into microbial natural products (NPs) present significant challenges for novices, largely due to the complexity of microbial systems, biochemical diversity, technical skill requirements, and the demands of bioinformatics and data analysis processes. To address these issues, we introduce ChatT2, a large language model (LLM)-based agent that is specifically tailored to the unique characteristics of bacterial type II polyketides. These polyketides form a structurally distinct and therapeutically important NP family. ChatT2 was developed within an autonomous multiagent framework composed of a mentor, an executor, and an evaluator, each with defined responsibilities. The mentor acts as an intermediary between ChatT2 and the user, utilizing chain-of-thought prompting to refine the intent of the user. Under the guidance of the mentor, the executor synthesizes multimodal information via retrieval-augmented generation techniques and seamlessly integrates bioinformatics and cheminformatics tools. The evaluator ultimately assesses the output of the executor to ensure the richness and accuracy of the retrieved information. Our research highlights how ChatT2, designed with this multiagent framework, addresses the challenges faced by general LLMs in terms of understanding limited, specialized corpora and complex biological information and provides both experts and novices with a valuable tool for exploring various NPs of interest. The ChatT2 webserver can be accessed at https://chatt2.site/#/chat.

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Latest papers 665