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ConRAG: Consensus-Driven Evidence Flow for Multi-Hop Question Answering
Retrieval-augmented generation (RAG) has emerged as a promising paradigm for enhancing large language models (LLMs) on multi-hop question answering (QA), which requires reasoning over evidence from multiple documents. However, current multi-hop RAG approaches still struggle with evidence selection a
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