3 papers
cs.CL2026
Human-Alignment, Calibration, and Activation Patterns in Large Language Model Uncertainty
Kyle Moore, Jesse Roberts, Daryl Watson +2
Uncertainty Quantification is a large and growing subfield of large language model behavioral analysis. Primarily to recognize and combat hallucination, the field has largely focus…
cs.CL2026
Human-Alignment and Calibration of Inference-Time Uncertainty in Large Language Models
Kyle Moore, Jesse Roberts, Daryl Watson
There has been much recent interest in evaluating large language models for uncertainty calibration to facilitate model control and modulate user trust. Inference time uncertainty,…
cs.CL2025
Investigating Human-Aligned Large Language Model Uncertainty
Kyle Moore, Jesse Roberts, Daryl Watson +1
Recent work has sought to quantify large language model uncertainty to facilitate model control and modulate user trust. Previous works focus on measures of uncertainty that are th…