Llm Multiagent Debate

Overview

Implements a multiagent debate system where multiple language model instances argue for their answers, then converge on a more factual and reasoned final response. Based on the ICML 2024 paper 'Improving Factuality and Reasoning in Language Models through Multiagent Debate'. Provides Python scripts to orchestrate debates between model instances.

Best for

Best for
Researchers and developers exploring debate-based self-correction for LLMs

Use cases

• Improving answer factualness for LLM outputs
• Reducing hallucination in generated text
• Enhancing reasoning accuracy via iterative debate

Notes

Implements a multiagent debate system where multiple language model instances argue for their answers, then converge on a more factual and reasoned final response. Based on the ICML 2024 paper ‘Improving Factuality and Reasoning in Language Models through Multiagent Debate’. Provides Python scripts to orchestrate debates between model instances.

543 stars on GitHub. Last updated 2025-04-24.

Use cases

• Improving answer factualness for LLM outputs
• Reducing hallucination in generated text
• Enhancing reasoning accuracy via iterative debate

Pros

• Straightforward implementation of a proven academic method
• Open-source and community-supported
• Modular design allows customization of debate rounds and models

Cons

• Requires multiple API calls per query increasing cost
• Relies on the quality of base models debates
• No official maintainer or commercial support

Indexed from awesome-ai-agents and enriched against its public facts.