MADBench: Benchmarking the Security of Multi-Agent Debate
Multi-agent debate (MAD) can improve large language model (LLM) reasoning by allowing multiple agents to exchange and critique their answers to the same task. However, the interactions that enable agents to correct mistakes can also spread adversarial errors and steer the agents toward an incorrect answer. Although som...
Yu-Wan Liu, Jia-Ming Zhang, Yue Huang et al.
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