Papers by Luzhe Sun

1 papers
HALP: Detecting Hallucinations in Vision-Language Models without Generating a Single Token (2026.eacl-long)

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Challenge: Existing methods for detection of hallucinations operate after text generation, making intervention costly and untimely.
Approach: They examine whether hallucination risk can instead be predicted before any token is generated by probing a model's internal representations in a single forward pass.
Outcome: The proposed model can detect hallucinations before token generation, while query-token representations can be more accurate.

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