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Reward on Path: Learning Intermediate Supervision Signals for Knowledge Graph Question Answering

Gao, Shengxiang et al.
arXiv (All) · Papers
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Knowledge Graph Question Answering (KGQA) aims to answer user questions by reasoning over Knowledge Graphs (KGs). Recent methods use supervision derived from answer labels or refined by Large Language Models (LLMs) to train models that retrieve KG evidence for LLM-based answer reasoning. However, an
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