Author

Jackie C. K. Cheung

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Open access Apr 2026

Confident in a Confidence Score: Investigating the Sensitivity of the Calibration of Confidence Scores to Supervised Fine-Tuning in Generation Tasks

Uncertainty quantification techniques measure confidence in language model outputs to support critical applications like hallucination detection and selective prediction. While prior work has developed various confidence metrics and demonstrated their calibration for classification tasks or using verbalized confidence,...

Lorenzo Jaime Yu Flores, Cesare Spinoso Di Piano, J. C. K. Cheung · The Proceedings of the Third... · 0 citations

#natural language process... Preprint Apr 2026

Confident in a Confidence Score: Investigating the Sensitivity of Confidence Scores to Supervised Fine-Tuning

It is found that calibration shifts substantially after SFT: across 216 configurations, it degrades in 112 cases and improves in 104, with confidence scores shifting due to factors beyond output quality, such as proximity to the training distribution.

Lorenzo Jaime Yu Flores, Cesare Spinoso di-Piano, Jackie C. K. Cheung · 0 citations