The Confident Liar: Diagnosing Multi-Agent Debate with Log-Probabilities and LLM-as-Judge

1. 1Build a multi-agent debate system using LLMs as judges
2. 2Run experiments to collect token-level log-probability distributions
3. 3Configure the system to assign rubric scores to reasoning tokens
4. 4Test the relationship between log-probabilities, rubric scores, and final task accuracy
5. 5Apply the findings to improve the quality of intermediate reasoning in debate systems

AI engineers and researchers on a team benefit from this micro-lesson as it helps them evaluate and improve the quality of multi-agent debate systems, and product managers can apply this knowledge to develop more accurate and reliable AI-powered debate tools

💡 Log-probabilities and LLM-as-judge rubric scores can be used to evaluate the quality of intermediate reasoning in multi-agent debate systems

🤖 Diagnose multi-agent debate systems with log-probabilities and LLM-as-judge! 💡