MARVEL: Modular Abstention for Reliable and Versatile Expert LLMs
A modular abstention framework for reliable expert LLMs that enables selective abstention from uncertain questions.
A modular abstention framework for reliable expert LLMs that enables selective abstention from uncertain questions.
Exploring psychological insights to address overconfidence in LLMs by comparing with human confidence patterns.
Automatic prediction of compute-optimal data composition for efficient LLM training.
Characterizing LLM abstention behavior in science QA with context perturbations.
Cross-class query network for partially labeled organ segmentation in medical images.
Learning metrics for evaluating recommendation explanations.