RioRAG uses nugget-centric verification with cross-source checks to create dense verifiable rewards for RL-based optimization of long-form RAG, yielding higher factual recall and faithfulness on LongFact and RAGChecker.
Clapnq: C ohesive l ong-form a nswers from p assages in natural questions for rag systems
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Reinforced Informativeness Optimization for Long-Form Retrieval-Augmented Generation
RioRAG uses nugget-centric verification with cross-source checks to create dense verifiable rewards for RL-based optimization of long-form RAG, yielding higher factual recall and faithfulness on LongFact and RAGChecker.