Papers by Tenny Yin

1 papers
Reasoning about Uncertainty: Do Reasoning Models Know When They Don’t Know? (2026.findings-eacl)

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Challenge: Reasoning models are prone to generating confident, plausible responses that are incorrect (hallucinations).
Approach: They introduce introspective uncertainty quantification to examine whether reasoning models are well-calibrated and does deeper reasoning improve their calibration?
Outcome: The proposed model calibrations show that models are overconfident, overconfent and overconfust with deeper reasoning.

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