AINeutralarXiv – CS AI · 10h ago6/10
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PathISE: Learning Informative Path Supervision for Knowledge Graph Question Answering
PathISE is a novel framework that enables knowledge graph question-answering systems to learn effective supervision signals from answer-level labels alone, eliminating the need for expensive intermediate annotations. By using a transformer-based estimator to identify informative relation paths and distilling them into LLM path generators, the approach achieves competitive state-of-the-art performance while reducing resource requirements for training.