JCQL uses an SLM-trained KBC model as an action in an LLM agent for KBQA to reduce hallucinations, then fine-tunes the KBC model with KBQA reasoning paths, outperforming baselines on two benchmarks.
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Joint Knowledge Base Completion and Question Answering by Combining Large Language Models and Small Language Models
JCQL uses an SLM-trained KBC model as an action in an LLM agent for KBQA to reduce hallucinations, then fine-tunes the KBC model with KBQA reasoning paths, outperforming baselines on two benchmarks.