Multi-Agent Consensus

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16 papers in the last four weeks, up 300% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 75

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Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy
May 13, 2026Adarsh Kumarappan, Ananya MujooAI Agent Reliability Multi-Agent LLM Systems
1California Institute of Technology · 2Evergreen Valley College
Effect of Graph Gluing on Consensus in Networked Multi-Agent Systems
May 11, 2026Rohollah Moghadam, Santosh KandelMulti-Agent Coordination Multi-Agent Systems
Department of Electrical and Electronic Engineering, California State University-Sacramento, 5028 Riverside Hall, 6000 J Street, Sacramento, CA, 95819, USA · Department of Mathematics and Statistics, California State University-Sacramento, 226 Brighton Hall, 6000 J Street, Sacramento, CA, 95819, USA
Robust Multi-Agent LLMs under Byzantine Faults
May 9, 2026Haejoon Lee, Vincent-Daniel Yun, Dimitra Panagou +1Multi-Agent LLM Systems Multi-Agent Coordination
Department of Robotics, University of Michigan, Ann Arbor, USA · Thomas Lord Department of Computer Science, University of Southern California, USA
Insider Attacks in Multi-Agent LLM Consensus Systems
May 8, 2026Xiaolin Sun, Zixuan Liu, Yibin Hu +1Multi-Agent LLM Systems Multi-Agent Systems
Department of Computer Science, Tulane University, New Orleans, United States of America.
The Cost of Consensus: Malignant Epistemic Herding and Adaptive Gating in Distributed Multi-Agent Search
May 7, 2026David Farr, Iain Cruickshank, Kate Starbird +1Opinion Dynamics Multi-Agent Systems
1*Information School, University of Washington, 1410 NE Campus Parkway, Seattle, 98195, WA, USA. · 2Computer Science, Carnegie Mellon University, 5000 Forbes Avenue,2026 Pittsburgh, 15213, PA, USA. · 3Human Centered Design Engineering, University of Washington, 1410 NE Campus Parkway, Seattle, 98195, WA, USA. +1
Adaptive Consensus in LLM Ensembles via Sequential Evidence Accumulation: Automatic Budget Identification and Calibrated Commit Signals
May 5, 2026Roberto E. MedinaLLM Inference Efficiency Multi-Agent Consensus
Independent Researcher
Learning to Act and Cooperate for Distributed Black-Box Consensus Optimization
May 1, 2026Zi-Bo Qin, Feng-Feng Wei, Tai-You Chen +1Multi-Agent System Optimization Multi-Agent Coordination
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China.
The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms
Apr 30, 2026Dahlia Shehata, Ming LiMulti-Agent LLM Systems Multi-Agent Coordination
University of Waterloo · Canada
The Cost of Consensus: Isolated Self-Correction Prevails Over Unguided Homogeneous Multi-Agent Debate
Apr 29, 2026Blaž Bertalanič, Carolina FortunaLLM Self-Correction AI Agent Evaluation
Jožef Stefan Institute Ljubljana, Slovenia
Preserving Disagreement: Architectural Heterogeneity and Coherence Validation in Multi-Agent Policy Simulation
Apr 29, 2026Ariel SelaMulti-Agent LLM Systems Multi-Agent Coordination
Tel Aviv University
TeamFusion: Supporting Open-ended Teamwork with Multi-Agent Systems
Apr 21, 2026Jiale Liu, Victor S. Bursztyn, Lin Ai +4Multi-Agent Coordination Multi-Agent Collaboration
Pennsylvania State University · Adobe Research · Columbia University +1
The Consensus Trap: Rescuing Multi-Agent LLMs from Adversarial Majorities via Token-Level Collaboration
Apr 18, 2026Jiayuan Liu, Shiyi Du, Weihua Du +2Multi-Agent LLM Systems Adversarial Robustness
Carnegie Mellon University · Foundations of Cooperative AI Lab (FOCAL) · Adelaide University
Auditing Multi-Agent LLM Reasoning Trees Outperforms Majority Vote and LLM-as-Judge
Feb 10, 2026Wei Yang, Shixuan Li, Heng Ping +3LLM Auditing Preference Optimization
University of Southern California
Generating consensus and dissent on massive discussion platforms with a semantic-vector model
Jan 20, 2026A. Ferrer, D. Muñoz-Jordán, A. Rivero +3Opinion Dynamics Computational Social Science
Instituto de Biocomputación y Física de Sistemas Complejos (BIFI), Universidad de Zaragoza, 50018 Zaragoza, Spain · Kampal Data Solutions, WTCZ, Avda. Maria Zambrano 31, 50018 Zaragoza, Spain · Departamento de Física Teórica, Universidad de Zaragoza, 50009 Zaragoza, Spain +2
The price of uncertainty for social consensus
Aug 24, 2025Yunzhe Bai, Alec SunOpinion Dynamics Multi-Agent Consensus

May 13, 2026, cs.LGJ/K move · Enter open · S save

Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy

Adarsh Kumarappan, Ananya Mujoo

1California Institute of Technology · 2Evergreen Valley College

AI Agent Reliability Multi-Agent LLM Systems LLM Sycophancy Adversarial Attacks on LLMs Multi-Agent Consensus Causal Interventions in Language Models

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LLM-based multi-agent pipelines flip from correct to incorrect answers under simulated peer disagreement at rates we term yield, a vulnerability widely attributed to RLHF-induced sycophancy. We test this attribution across four model families and find it largely wrong: pretrained base models exhibit the same substitution pattern as their Instruct variants, averaging higher yield than Instruct. Using activation patching, we localize the corruption to a narrow mid-layer window where attention carries the causal weight and MLP contribution is negligible; patching above this window restores 96% of the clean-to-pressured P(correct) gap. The attack surface decomposes into two independent factors (channel framing and consensus strength) whose interaction produces a 47.5 percentage-point yield gap at majority consensus, preserved across jury sizes

N \in \{4, 5, 6\}

. Two converging activation-space interventions show that pressure suppresses clean-reasoning features rather than activating a new sycophancy circuit. A single correctly-arguing dissenter reduces yield by 54-73 percentage points across all framings tested, whereas the strongest prompt-level defense fails on attack variants outside its design surface. Mitigations should target the mechanism, structured dissent at the pipeline level, rather than prompt-level defenses.

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