2 papers
cs.LG2026
Integrating Local and Global Entropy for Uncertainty Quantification in LLMs
Johanne Medina, Tianyi Zhou, Keivin Isufaj +2
Large language models hallucinate confidently, making uncertainty quantification (UQ) essential for reliable deployment. Existing methods rely predominantly on token-level signals,…
cs.CL2025
Can LLMs Detect Their Confabulations? Estimating Reliability in Uncertainty-Aware Language Models
Tianyi Zhou, Johanne Medina, Sanjay Chawla
Large Language Models (LLMs) are prone to generating fluent but incorrect content, known as confabulation, which poses increasing risks in multi-turn or agentic applications where…