2 papers
cs.LG2025
Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
Maya Kruse, Majid Afshar, Saksham Khatwani +3
Large language models (LLMs) often behave inconsistently across inputs, indicating uncertainty and motivating the need for its quantification in high-stakes settings. Prior work on…
cs.AI2024
Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability
Yanjun Gao, Skatje Myers, Shan Chen +7
Large language models (LLMs) are being explored for diagnostic decision support, yet their ability to estimate pre-test probabilities, vital for clinical decision-making, remains l…