Papers by Qiang Duan
Revisiting the Self-Consistency Challenges in Multi-Choice Question Formats for Large Language Model Evaluation (2024.lrec-main)
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| Challenge: | Multi-choice questions (MCQs) are a common method for assessing the world knowledge of large language models. |
| Approach: | They propose three knowledge-equivalent question variants to assess LLMs' world knowledge . they propose option position shuffle, option label replacement, and conversion to a True/False format . |
| Outcome: | The proposed questions are shuffle, label replacement, and True/False format. |
Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding (2026.findings-acl)
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Weixu Zhang, Fanghua Ye, Qiang Gao, Jian Li, Haolun Wu, Yuxing Tian, Sijing Duan, Nan Du, Xiaolong Li
| Challenge: | Large language models produce content that contradicts or overlooks information provided in the input context, a phenomenon known as faithfulness hallucination. |
| Approach: | They propose a lightweight framework that boosts the generation probability of context-relevant tokens by boosting the generation of tokens. |
| Outcome: | The proposed framework improves faithfulness metrics with minimal generation overhead. |
LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries (2026.findings-acl)
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| Challenge: | Existing refusal strategies for unanswerable and underspecified user queries are brittle due to model hallucinations or add complexity and overhead. |
| Approach: | They propose a latent-signal refusal mechanism that predicts query answerability from hidden activations of an LLM. |
| Outcome: | The proposed scheme reduces schema noise and sparse, localized question–schema mismatch cues that indicate unanswerability. |