Good Papers

Showing Multi-agent LLM systems Show all papers

88%Must read
?Must readVote to see the score
arXivMulti-agent LLM systems

Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction

SHIFT predicts harness utility via a local LLM to search multi-agent structures per query, achieving ~80% mean accuracy across benchmarks while reducing execution tokens by 32%.

Som Sagar, Shasha Li, Hejie Cui, Ransalu Senanayake and 1 more

Published Oct 2, 2026 · ▲ 10 on Hugging Face

– ReadersNo votes yet
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 3/5
83%Must read
?Must readVote to see the score
arXivGeorgia Institute of TechnologyU California, Los AngelesU ChicagoMulti-agent LLM systems

Science Utopia? Closed-Loop LLM Simulation of Academic Research Ecosystems

SciUtopia is a closed-loop LLM simulation framework modeling entire academic ecosystems; it finds resubmission amplifies reviewer burden, cautious exploration balances impact and diversity, and inequality can emerge without cumulative funding advantage.

Yiqiao Jin, Yiyang Wang, Lucheng Fu, Bing He and 7 more

Published Oct 1, 2026 · 0 citations · ▲ 40 on Hugging Face · Code ★ 29

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 2/5
74%Highly rated
?Highly ratedVote to see the score
arXivMulti-agent LLM systems

Understanding Issues, Causes and Solutions in Open-Source LLM-based Multi-Agent Systems

Open-source LLM multi-agent systems face orchestration and execution issues mostly caused by workflow, tool integration, and memory problems, primarily solved by workflow optimization.

Asad Ur Rehman, Syed Mohammad Kashif, Ruiyin Li, Peng Liang and 2 more

Published Oct 1, 2026 · 0 citations

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 1/5
72%Highly rated
?Highly ratedVote to see the score
arXivMulti-agent LLM systems

Auditing Action Settlement in LLM Agent Environments: Order, Progress, and Replay

A typed settlement contract audits concurrent LLM agent actions, showing joint policies complete 59% more six-agent doorway tasks than conservative rejection, with exact replay of 156 checkpoints and rejection of 1,332 corruptions.

Haotian Chen, Bowen Ye, Yuning Zhang, Jingkun Yu

Published Oct 1, 2026 · 0 citations

– ReadersNo votes yet
8/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 8 of 20 reviewers recommend it
lenient 3/5
medium 3/10
strict 2/5
78%Highly rated
?Highly ratedVote to see the score
arXivMulti-agent LLM systems

Raven: The Harness of Harnesses for Composable Agentic Intelligence

Raven autonomously constructs modular agent harnesses and orchestrates them across domains via a multi-agent ecosystem, significantly outperforming state-of-the-art systems on complex long-horizon tasks.

EverMind AI

Published Sep 27, 2026 · 0 citations · ▲ 566 on Hugging Face · Code ★ 5,252

– ReadersNo votes yet
11/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
83%Must read
?Must readVote to see the score
arXivColumbiaAmazonMulti-agent LLM systems

Receiver-Conditioned Latent Communication gives 94% CacheBack

CacheBack uses receiver-conditioned filtering of sender KV caches via attention weights to cut transferred state by 75%, boosting multi-agent accuracy by 14.7 points and reducing latency 3.2x versus text.

Maximillian Rossi, Prajwal Raghunath, Haoqing Xuan, Yusen Zhang and 1 more

Published Sep 25, 2026 · 0 citations · ▲ 11 on Hugging Face · Code ★ 6

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5
74%Highly rated
?Highly ratedVote to see the score
arXivShanghai Jiao TongShanghai Innovation InstituteMulti-agent LLM systems

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

ARIS is an open-source autonomous research harness using cross-model adversarial collaboration to coordinate ML workflows and verify experimental claims.

Ruofeng Yang, Yongcan Li, Shuai Li

Published May 4, 2026 · 1 citation · ▲ 154 on Hugging Face · Code ★ 17,051

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
86%Must read
NeurIPS 2026Multi-agent LLM systems

Recursive Multi-Agent Systems

RecursiveMAS scales multi-agent collaboration through recursive latent-space computation via RecursiveLink and inner-outer loop co-optimization, improving accuracy by 8.3% with 1.2-2.4x speedup and 34.6%-75.6% token reduction over baselines.

Jiaru Zou, Rui Pan, Ruizhong Qiu, Pan Lu and 7 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published Apr 28, 2026 · 0 citations · ▲ 239 on Hugging Face · Code ★ 961

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
76%Highly rated
?Highly ratedVote to see the score
arXivMulti-agent LLM systems

Kimi K2.5: Visual Agentic Intelligence

Kimi K2.5 is an open-source multimodal agentic model using joint text-vision optimization and Agent Swarm to achieve state-of-the-art agentic, coding, vision, and reasoning results with up to 4.5x lower latency.

Kimi Team, Tongtong Bai, Yifan Bai, Yiping Bao and 36 more

Published Feb 2, 2026 · 2 citations · ▲ 277 on Hugging Face · Code ★ 2,313

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 1/5
71%Highly rated
?Highly ratedVote to see the score
arXivMulti-agent LLM systems

PaperBanana: Automating Academic Illustration for AI Scientists

PaperBanana automates publication-ready academic illustrations via agentic VLM and image generation, outperforming baselines on a 292-case benchmark.

Dawei Zhu, Meng, Rui, Yale Song, Xiyu Wei and 3 more

Published Jan 30, 2026 · 1 citation · ▲ 230 on Hugging Face · Code ★ 7,132

– ReadersNo votes yet
7/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 7 of 20 reviewers recommend it
lenient 4/5
medium 3/10
strict 0/5
70%Highly rated
?Highly ratedVote to see the score
PreprintU California, Los AngelesMassachusetts Institute of TechnMulti-agent LLM systems

TradingAgents: Multi-Agents LLM Financial Trading Framework

TradingAgents proposes a multi-agent LLM framework with specialized trading roles and collaborative dynamics, outperforming baselines on cumulative returns, Sharpe ratio, and drawdown.

Xiao, Yijia, Edward W. Sun, Luo, Di, Wei Wang

Published Dec 28, 2024 · 6 citations · ▲ 150 on Hugging Face · Code ★ 110,044

– ReadersNo votes yet
5/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 5 of 20 reviewers recommend it
lenient 4/5
medium 1/10
strict 0/5
71%Highly rated
?Highly ratedVote to see the score
arXivRenmin University of ChinaMulti-agent LLM systems

Very Large-Scale Multi-Agent Simulation in AgentScope

AgentScope introduces actor-based distributed infrastructure, flexible environments, and automated agent generation to enable scalable, efficient multi-agent simulations.

Xuchen Pan, Gao, Dawei, Yuexiang Xie, Chen, Yushuo and 5 more

Published Jul 25, 2024 · 1 citation · ▲ 47 on Hugging Face · Code ★ 32,834

– ReadersNo votes yet
6/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 6 of 20 reviewers recommend it
lenient 4/5
medium 2/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Department of Computer Science, Salesforce AI ResearchSalesforce ResearchU Wisconsin, MadisonMulti-agent LLM systems

SkillOrchestra: Learning to Route Agents via Skill Transfer

Jiayu Wang, Yifei Ming, Zixuan Ke, Shafiq Joty and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U CambridgeU Colorado Anschutz Medical CampU Colorado School of MedicineMulti-agent LLM systems

Open-Ended Scientific Discovery and the Social Dynamics of Evolving Agent Networks

Tennison Liu, Silas Ruhrberg Estévez, Rob Davis, Ryan M Sheridan and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Nanyang TechnologicalNanyang Technological UniversityMulti-agent LLM systems

Social Interaction Breaks Replicate Independence in Controlled-Clone LLM Agents

Yandan Zheng, Haoran Luo, Anh Tuan Luu

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Massachusetts Institute of TechnU ZurichETHZ - ETH ZurichGoogle DeepMind & MITMulti-agent LLM systems

Belief Engine: Configurable Stance Dynamics for Multi-Agent LLM Deliberation

Joshua C Yang, Maurice Flechtner, Damian Dailisan, Michiel Bakker

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026U Southern CaliforniaIntel LabsNorthwesternIntelCarnegie MellonMulti-agent LLM systems

TritonTune: LLM-Guided Multi-Agent Optimization of GPU Kernel Configurations

Shukai Duan, Mihai Capotă, Guixiang Ma, Hou-Jen Ko and 4 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026New Jersey Institute of TechnoloU North Carolina at Chapel HillU Electronic Science and TechnolShandong University of North Carolina atMulti-agent LLM systems

UMAS: System-Level Uncertainty Quantification for Multi-Agent LLM Systems

Hanwen Li, Jinhao Duan, Xiaoshuang Shi, Yue Zhang and 3 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026UCSDU California, San DiegoRiceNortheasternQuEra Computing Inc.Multi-agent LLM systems

Qubrio: High-Performance Quantum Compilation via Multi-Agent LLM Collaboration

Jixuan Ruan, Zhuo Cui, Zhengding Hu, Zhongkai Yu and 9 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Korea Advanced Institute of ScieKAISTMulti-agent LLM systems

Multi-Agent Coordination via Support-Preserving Distillation

Sangmin Lee, Youngju Na, Chanmi Lee, Sung-eui Yoon

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026The University of EdinburghU MacauThe Chinese University of Hong KMulti-agent LLM systems

Veri-Sure: Multi-Agent RTL Code Generation with Temporal Tracing, Slicing and Formal Verification

Jiale Liu, Taiyu Zhou, Tianqi Jiang

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026ChongqingChina Mobile Group Guizhou CompaMulti-agent LLM systems

OrchestraRL: Learning to Orchestrate LLM Agent Swarms with Entropy-Aware Communication Control

Runze Fan, Shiyi Jiang, Junsheng Wang, Shuangjun Xie and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Dartmouth CollegeVirginia TechNew YorkMulti-agent LLM systems

Optimize Once, Execute Fast: Latency-Aware Multi-Agent Workflow Learning for Recurrent Queries

Enpei Zhang, Feiyu Qu, Zheng Huang, Dawei Zhou and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Beijing University of Post and TBeijing University of Posts and Multi-agent LLM systems

Behavioral Probes for Information Flow in LLM Swarms

Junhui Chen, Yu Zhang, Lantian Li, Dong Wang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026GoogleGoogleMulti-agent LLM systems

SCHOLARPEER: A Multi-Agent Framework for Automated Peer Review

Palash Goyal, Mihir Parmar, Yiwen Song, Hamid Palangi and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026SoutheastWuhanLa TrobeU WollongongMulti-agent LLM systems

Integrating Strengths of Different Multi-Agent Workflows via Step-Aware Hybrid Topology Planning

Jingxuan Yu, Ju Jia, Yiqian Chen, Yuchong Chen and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026OralShanghai Jiao TongShanghai JiaotongHuawei Technologies Ltd.Shanghai Jiao Tong UnviersityMulti-agent LLM systems

SMART: Scalable Multi-Agent Role-conditioned Teaming via LLM-free Tree Search

Runzhe Zhang, Ning Li, Xingshan Zeng, Letian Chen and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Illinois at Urbana-ChampaignRutgersSalesforce AI ResearchUIUCMulti-agent LLM systems

When Debate Helps: Proposal Supply and Verification-Aware Readout in Multi-Agent Reasoning

Zihao Zhao, Tunyu Zhang, Haizhou Shi, Yusong Zhao and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026RutgersU Illinois at Urbana-ChampaignSalesforce AI ResearchGoogle DeepMindAmazonMulti-agent LLM systems

Sequential Probabilistic Uncertainty Estimation for Parallel Multi-Agent Reasoning Systems

Tunyu Zhang, Zihao Zhao, Yusong Zhao, Haizhou Shi and 4 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Beijing University of AeronauticNanyang TechnologicalTsinghuaChina TelecomTsinghua University, TsinghuaMulti-agent LLM systems

EvoInspect: A Unified Self-Evolving Multi-Agent Framework for Industrial Hardware Inspection

Zhuyun Yuan, Jiming Zhang, Haoyuan Sun, Jun Yin and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U California - Los AngelesU California, Los AngelesYaleMax Planck Institute for SoftwarMulti-agent LLM systems

Youdunit: Single-Call Counterfactual Necessity in Multi-Agent LLM Systems

Marissa Li, Stephanie Gao, Kenny Guo, Xingjian Li and 2 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U California, San DiegoUC San DiegoMulti-agent LLM systems

Mental-Models for Multi-Agent Systems

Hanan Gani, Lulu Shao, Manmohan Chandraker

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026WuhanMulti-agent LLM systems

MASTA: A Feedback-Scheduled Multi-Agent System for End-to-End Tamarin Protocol Modeling and Analysis

Yongkang Xiao, Qiyi Deng, Jing Chen, Min Shi and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Central FloridaAmazonMulti-agent LLM systems

MaRiO: Multi-agent Collaborative Reasoning via Shared Observations in MLLMs

Nathaniel Redmond, Fidel Omar Tito Cruz, Devansh Sharma, Shehreen Azad and 3 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026SpotlightTsinghuaMicrosoftU TorontoMassachusetts Institute of TechnResearch, MicrosoftMulti-agent LLM systems

STAR-Math: Multi-Agent Mathematical Reasoning under Persistent Meta-Strategic Supervision

Jiaao Wu, Xian Zhang, Hanzhang Liu, Sophia Zhang and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026OxfordAlleloCooperative AI FoundationUppsalaUK AI Security InstituteMulti-agent LLM systems

Inter-Agent Influence: Evaluating Persuasion, Deception and Coercion in Multi-Agent Systems

Chandler Smith, Cecilia E Tilli, Qi Guo, Sophia Hatz and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U FloridaU OklahomaOak Ridge National LaboratoryArgonne National LaboratoryUnited States Military AcademyMulti-agent LLM systems

Unified Resource-Grounded Coordination Protocol for Orchestrator-Free Heterogeneous Multi-Agent Systems

Vishal Pramanik, Maisha Maliha, Olivera Kotevska, Arvind Ramanathan and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U OklahomaMulti-agent LLM systems

Spend Only What You Need: Defect-Aware Residual Coverage for Efficient Multi-Agent Reasoning

Maisha Maliha, Dean F Hougen

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026WuhanU DenverMulti-agent LLM systems

CacheMAS: Cache Communication for Single-Pass, Jointly-Optimized Multi-Agent Systems

Chao Ouyang, Yuyang Bai, Jun Zhang, Tianlu Gao and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026SoutheastSEUHuawei Technologies Ltd.Multi-agent LLM systems

Complex Optimization Modeling via Multiagent Fine-Tuning and Skill-Augmented Reasoning

Yu Ding, Jiajun Li, Ran Hou, Jiahui Duan and 6 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026SoutheastMulti-agent LLM systems

Effective Knowledge Conflict Detection via Joint Agentic Optimization

Yi Hong, Wenchao Bai, Jiaqi Jiang, Siyuan Huang and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Nanyang TechnologicalNational University of SingaporeJD Explore AcademyA*STARU SydneyMulti-agent LLM systems

FlowLeak: Coverage-Guided Extraction of Dynamic Workflows in LLM-Based Multi-Agent Systems

Zhiyao Ren, Siyuan Liang, Yibing Zhan, Jun L Tan and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Nanyang TechnologicalMulti-agent LLM systems

WURI: Watching Unfolding Risk in Agent Interactions

Yiyang Duan, Tiantong Wu, Yurong Hao, Wei Yang Bryan Lim

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Huazhong University of Science aThe Hong Kong PolytechnicNanjing University of Posts and MBZUAIMulti-agent LLM systems

Who Should Evolve? Uncertainty-Aware Role Bottleneck Inference for Multi-Agent LLM Training

Qiyu Qin, Yichen Li, Haozhao Wang, Tianzhe Xiao and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026KAUSTKing Abdullah University of ScieMulti-agent LLM systems

The Reflexivity Threshold: A Phase Transition for Multi-Agent Performative Prediction

Ahmed Mahrous, Roberto Di Pietro

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026TianjinU MacauMacau University of Science and Institute of automation, ChineseZhejiangMulti-agent LLM systems

LocalAgent: Collaborative Agentic Verification for Fine-Grained Instance-Level Consistency

jiachen Guo, Xinshan Zhu, Boyun Wang, Yanyan Liang and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026U OxfordU Oxford, Meta AIJD.comMulti-agent LLM systems

Zero-Shot Coordination among LLM Agents

Adrian Hayler, Shashank Reddy Chirra, Andrei Lupu, Johannes Forkel and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026East China NormalHuazhong University of Science aTsinghuaMulti-agent LLM systems

When the Most Disruptive Messages Are Safe to Prune in Aggregate: Functional Analysis of Communication Pruning in Two-Agent LLM Systems

Zhen Sun, Xueyang Zhou, Yongchao Chen

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U California, BerkeleyUC Berkeley / NVIDIA ResearchUniversity College LondonUC BerkeleyMulti-agent LLM systems

From Chats to Markets: AgenticPay for LLM-Powered Negotiation in Multi-Agent Commerce

Xianyang Liu, Shangding Gu, Fan Xu, Manxi Wu and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U OxfordU California, BerkeleyMulti-agent LLM systems

Ad-Hoc Teamwork from Human Demonstrations

Darius Muglich, Niklas Lauffer, Tin Dizdarević, Jakob Foerster

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026MicrosoftMicrosoft ResearchGoogle DeepmindMicrosoft Research AsiaMulti-agent LLM systems

The Era of Agentic Organization: Learning to Organize with Language Models

Zewen Chi, Li Dong, Qingxiu Dong, Yaru Hao and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U LouisvilleU North TexasMulti-agent LLM systems

Who, Where, and What? Forensic Localization in LLM-Based Multi-Agent Systems

ANJUN GAO, Yueyang Quan, Yufei Xia, Zhuqing Liu and 1 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U California, BerkeleyUC BerkeleyMulti-agent LLM systems

Evolving Agent Teams

Shiyi Cao, Ziming Mao, Dacheng Li, Joseph Gonzalez and 1 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Department of Computer Science, Univ of OxfordMulti-agent LLM systems

Online Learning of Group-Stable Coalition Structures

Saar Cohen, Michael Wooldridge

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026TsinghuaShenzhen Institutes of Advanced SichuanShenzhen Institutes of Advanced Multi-agent LLM systems

Learning When to Collaborate: Selective Multi-Agent Medical Reasoning via Uncertainty-Aware Routing

Jiacheng Hou, Xueliang Cui, Dan Lu, Ruxin Wang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026WuhanMulti-agent LLM systems

Market-Based Runtime Resource Allocation for LLM Multi-Agent Systems

Yixue Huang, Mingxin Wang, Hao Li, Hao Jiang

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Ant GroupU Electronic Science and TechnolU ChicagoU Southern CaliforniaMulti-agent LLM systems

Overcoming Attention Distraction: Training-Free Latent Communication for Multi-Agent Systems

zhengjie zhou, Yahao Liu, Ziyue Feng, Tengfei LIU and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
88%Must read
?Must readVote to see the score
NeurIPS 2026Georgia Institute of TechnologyMetaFacebookMulti-agent LLM systems

Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows

Parallel-Synthesis lets LLM synthesizers consume parallel agents' KV caches directly via a cache mapper and adapter, matching text synthesis on seven of nine benchmarks while cutting time-to-first-token by 2.5x-11x.

Shikun Liu, Mufei Li, Dongqi Fu, Haoyu Wang and 4 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5
88%Must read
?Must readVote to see the score
NeurIPS 2026Oregon StateJohnson and JohnsonPennsylvania StateMulti-agent LLM systems

EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales

EVOCHAMBER enables training-free multi-agent test-time co-evolution across individual, team, and population scales via asymmetric cross-agent knowledge transfer, achieving up to 32% relative math gains and emergent specialization.

Yaolun Zhang, Tianyi Xu, Shengyu Dai, Zhenwen Shao and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 10 on Hugging Face · Code ★ 4

– ReadersNo votes yet
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 2/5
Show 20 more papers