3 papers
cs.AI2026
ConfidenceBench: Evaluating Confidence Calibration in Large Language Models
Matthew ffrench-Constant, Daniel Yang, Xinmeng Huang +1
Large language models (LLMs) are increasingly deployed in settings where fluent but incorrect answers can be costly. In these settings, accuracy alone is insufficient: models must…
cs.LG2025
Compute-Optimal LLMs Provably Generalize Better With Scale
Marc Finzi, Sanyam Kapoor, Diego Granziol +4
Why do larger language models generalize better? To investigate this question, we develop generalization bounds on the pretraining objective of large language models (LLMs) in the…
cs.CV2023
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification
L. Julian Lechuga Lopez, Tim G. J. Rudner, Farah E. Shamout
Machine learning-aided clinical decision support has the potential to significantly improve patient care. However, existing efforts in this domain for principled quantification of…