Papers by Zhihui Lu

2 papers
Rethinking Multiple-Choice Questions for RLVR: Unlocking Potential via Distractor Design (2026.findings-acl)

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Challenge: Existing approaches to RLVR use multiple-choice questions as verifiable rewards . however, not all tasks provide reliable verification .
Approach: They propose a framework that actively constructs high-quality distractors to block elimination shortcuts and promote deep reasoning.
Outcome: The proposed method significantly improves reasoning capabilities of Large Language Models.
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.

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