The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate

arXiv:2608.22152 · cs.CL · Submitted 2026-08-23 · Read on arXiv

cs.CL

Submitted: 2026-08-23

Updated: 2026-09-22

Terminology

• Grounding — 27× in this paper · explained in 3 episodes
• Superadditivity — 9× in this paper · explained in 2 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Cooperation — 5× in this paper · explained in 2 episodes
• Multi-Agent System — 4× in this paper · explained in 5 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Annotator Agreement — 3× in this paper · explained in 1 episode
• Shapley values — 3× in this paper · explained in 2 episodes
• Task Decomposition — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Affordance — 1× in this paper · explained in 1 episode
• Agentic Task — 1× in this paper · explained in 1 episode
• Agentic Tasks — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Commentary — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Entanglement — 1× in this paper · explained in 3 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Multi-agent Collaborative Framework — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Topological Order — 1× in this paper · explained in 2 episodes

Sources

• The Collaboration Gap: Exploration and Benchmarking of Open-World Agentic Cooperation
• MT-PingEval: Evaluating Multi-Turn Collaboration with Private Information Games
• Large Language Model based Multi-Agents: A Survey of Progress and Challenges
• Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?
• PreScam: A Benchmark for Predicting Scam Progression from Early Conversations
• Grounded Misunderstandings in Asymmetric Dialogue: A Perspectivist Annotation Scheme for MapTask
• Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents
• More Capable, Less Cooperative? When LLMs Fail At Zero-Cost Collaboration
• Mora: Enabling Generalist Video Generation via A Multi-Agent Framework
• SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering