Byzantine Cheap Talk: Adversarial Resilience and Topology Effects in LLM Coordination Games
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Multi-agent LLM systems increasingly rely on communication protocols for coordination, yet their robustness under adversarial and structural constraints remains poorly understood. Building on prior work showing that cheap-talk channels enable cooperation in LLM coordination games, we investigate two vulnerability classes in a 4-player Stag Hunt across six model families and 720 trials. First, when Byzantine agents signal cooperation but defect, non-Byzantine agents detect the betrayal within one round yet fail to adapt collectively: a substantial fraction continue cooperating despite repeated exploitation, unable to recover coordination due to the game's unanimity payoff structure. Second, explicitly restricting communication topology collapses cooperation, while applying identical restrictions silently preserves near-perfect cooperation. This establishes that coordination failure stems from agents' meta-reasoning about hidden information, not information loss itself. We identify two stable behavioral archetypes that replicate across all model cohorts: Defection-Prone models that switch permanently after betrayal, and Cooperation-Persistent models that continue cooperating at significant individual cost. These findings reveal concrete security vulnerabilities: communication channels can be exploited as adversarial injection vectors, and disclosing network topology to agents can degrade coordination even without any adversary present.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 8 of its 22 references that are in the map. First posted on arXiv 5 Jun 2026.
Builds on
8 of 22 references.
Closest ancestors · 1
Same direction, newest first
- 2025Communication Enables Cooperation in LLM Agents: A Comparison with Curriculum-Based Approaches7 Oct
Other references · 7
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Citing papers per year: 2026: 3.
3 papers.
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- 2026Re-derivability Decides What a Staged Agent Pipeline Recovers After an Upstream Fault26 Sep 2026
- 2026Connecting the Dots in Agentic AI Security: A Cross-Dimensional Threat Taxonomy, Evaluation Maturity, and Open Challenges20 Sep 2026
- 2026SoK: When Safe Agents Fail Together: The Security of Multi Agent LLM Systems1 Sep 2026
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