Papers by Guanting Luo

2 papers
ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models (2024.findings-acl)

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Challenge: Existing KBQA methods address inefficient knowledge retrieval and semantic parsing errors.
Approach: They propose a generatethen-retrieve KBQA framework that generates logical form and replaces entities and relations with an unsupervised retrieval method to improve both generation and retrieval more directly.
Outcome: Experimental results show that ChatKBQA achieves new state-of-the-art performance on standard KBQA datasets, WebQSP, and CWQ.
Applicability Condition Extraction for Therapeutic Drug-Disease Relations (2026.findings-acl)

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Challenge: Existing methods for identifying conditions under which a drug can be effective are limited . et al., j. n. d., al. c., and dr. m. s., 2005, are not able to identify context-specific conditions for therapeutic drug–disease relations.
Approach: They propose to annotate triples of drugs, diseases, and applicability conditions from biomedical literature.
Outcome: The proposed method outperforms baselines across evaluation settings.

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