AI RESEARCH
KBQA-R1: Reinforcing Large Language Models for Knowledge Base Question Answering
arXiv CS.CL
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ArXi:2512.10999v3 Announce Type: replace Knowledge Base Question Answering (KBQA) challenges models to bridge the gap between natural language and strict knowledge graph schemas by generating executable logical forms. While Large Language Models (LLMs) have advanced this field, current approaches often struggle with a dichotomy of failure: they either generate hallucinated queries without verifying schema existence or exhibit rigid, template-based reasoning that mimics synthesized traces without true comprehension of the environment.