Research map / Multi-agent systems and games / LLM agents
AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators
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Introduces AgentCollabBench, a 900-task diagnostic benchmark measuring four behavioral failure modes (instruction decay, tracer durability, consensus pollution, cross-task leakage) in multi-agent LLM systems across communication topologies, evaluating four LLMs.
Problem
Outcome-based evaluations of multi-agent LLM systems miss process-level failures such as dropped constraints, lost information across hops, false-belief spread, and cross-task leakage.
Approach
A controlled-injection benchmark with four deterministic/LLM-judged metrics (IDR, RTD, CPR, CLC) stratified across domains, topologies, and complexity tiers, plus a finding that converging-DAG nodes drop constraints from minority parent branches.
Key results
- Qwen-3.5-35B-A3B leads on tracer durability (RTD 94.0%) and instruction decay (IDR 0.9%), while GPT 4.1 mini has the lowest cross-task leakage (CLC 2.6%) and consensus pollution (CPR 17.7%).
- Topology explains 7-40% of variance (eta^2 = 0.07-0.40) in RTD; converging-DAG hops drop tracers at 1.6-5.0x the rate of linear-chain hops.
- Llama 3.1 8B Instruct is worst on three of four metrics (IDR 10.1%, CPR 40.3%, RTD 62.6%).
Surprising findings
- Converging-DAG topology causes substantially higher constraint loss than linear chains across all four models, with effect size comparable to backbone choice.
- Structural complexity tiers are largely orthogonal to behavioral failure rates; CLC even decreases with complexity for GPT 4.1 mini.
Limitations
- Coverage limited to three domains and five fixed topologies.
- Potential evaluator bias from LLM-judged metrics (IDR, CPR) despite judge-backbone separation.
- No analysis of correlation between metrics and task success.
Experimental setup
Datasets: AgentCollabBench
Benchmarks: AgentCollabBench
Metrics: Instruction Decay Rate Radioactive Tracer Durability Consensus Pollution Rate Cross-task Leakage Containment Cohen's kappa Spearman correlation Kruskal-Wallis eta-squared
Baselines: Chatbot Arena leaderboard ranks
Builds on: MultiAgentBench GEMMAS MAST
Closest papers by meaning
- Towards a Science of AI Agent Reliability (ICML 2026 · similarity 0.89)
- DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems (ICLR 2026 · similarity 0.89)
- On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents (ICML 2025 · similarity 0.88)
- The Best-Laid SCHEMEs: Coordinated Sabotage and Monitoring in Multi-Agent Systems (NeurIPS 2026 · similarity 0.88)
- AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems (NeurIPS 2026 · similarity 0.88)
- AgentHijack: Benchmarking Computer Use Agent Robustness to Common Environment Corruptions (ICML 2026 · similarity 0.88)
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