Papers by Dechang Kong
Seeking Rational Demonstrations for Large Language Models: A Domain Generalization Approach to Unsupervised Cross-Domain Keyphrase Generation (2025.acl-short)
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| Challenge: | Unsupervised cross-domain keyphrase generation is crucial in real-world natural language processing scenarios, but its accuracy is limited by the distribution shift between source and target domain. |
| Approach: | They propose to seek rational demonstrations from the source domain and to use them to improve their ability in the unsupervised cross-domain keyphrase generation setting. |
| Outcome: | The proposed model achieves state-of-the-art on widely used cross-domain KG benchmarks and the results are published in the journal Nature. |
TrustTable: A Neuro-Symbolic Auditing Framework for Faithful Table QA (2026.acl-long)
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| Challenge: | Large Language Models (LLMs)-based TableQA models exhibit unfaithful behavior where correct answers are derived through erroneous reasoning paths. |
| Approach: | They propose a neuro-symbolic framework to audit LLM reasoning processes . it enforces factual grounding and ensures logical soundness by verifying reasoning chains . |
| Outcome: | The proposed framework outperforms LLM judges in majority voting and rejection sampling with process supervision. |