SiGIR trains a language model to decompose multi-hop questions, self-critique each retrieval and reasoning step, and use cumulative self-rewards in a beam search, beating prior methods by up to 14.4 F1 points on MuSiQue.
Rae, Erich Elsen, and Laurent Sifre
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Self-Critique Guided Iterative Reasoning for Multi-hop Question Answering
SiGIR trains a language model to decompose multi-hop questions, self-critique each retrieval and reasoning step, and use cumulative self-rewards in a beam search, beating prior methods by up to 14.4 F1 points on MuSiQue.