Multi-agent Scaling Across Disjunctive and Compensatory Tasks

arXiv:2609.31563 · cs.AI, cs.MA · Submitted 2026-09-25 · Read on arXiv

cs.AI, cs.MA

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Accuracy — 63× in this paper · explained in 1 episode
• Benchmark — 21× in this paper · explained in 2 episodes
• Aggregation — 13× in this paper · explained in 1 episode
• Verifier — 11× in this paper · explained in 2 episodes
• Large Language Model — 5× in this paper
• Benchmarking — 3× in this paper · explained in 3 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 3× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 2× in this paper
• Scaffolding — 2× in this paper · explained in 3 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• Systematic Bias — 2× in this paper · explained in 3 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Agentic Coding — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Divergent Association Task — 1× in this paper
• Empirical Methods in Natural Language Processing — 1× in this paper
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Thinking mode — 1× in this paper · explained in 2 episodes
• Verifiability — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• The Ringelmann Effect in Multi-Agent LLM Systems: A Scaling Law for Effective Team Size
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Training Verifiers to Solve Math Word Problems
• LLMs are Overconfident: Evaluating Confidence Interval Calibration with FermiEval
• LLM for Complex Reasoning Task: An Exploratory Study in Fermi Problems
• Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity

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