Papers by Sijing Qin

    1 papers
    Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge (2026.acl-long)

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    Challenge: Large language models (LLMs) are increasingly used as automated evaluators . et al., 2024: strong labels can foster trust but also undermine it .
    Approach: They show that LLMs' source labels bias trust judgments by humans . they use eye-tracking data to analyze LLM internal states during judgment .
    Outcome: The proposed model is biased by disclosed source labels, the authors show . eye-tracking data show humans rely heavily on source labels for judgments .

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