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SEPAL: Separated Expert Pairs with Answer-Level Fusion for Reliable LLM Collaboration
Multi-agent collaboration lets large language models (LLMs) improve question answering through deliberation and feedback. Yet shared discussion couples correction with exposure to the same mistakes, which can erode the diversity needed for voting. Self-consistency offers sampling diversity without f
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