11 citations · 36 across the 18 of their papers we have counts for
3 papers · 1 filter
Comprehensiveness Metrics for Automatic Evaluation of Factual Recall in Text Generation
Adam Dejl, James Barry, Alessandra Pascale +1
Despite demonstrating remarkable performance across a wide range of tasks, large language models (LLMs) have also been found to frequently produce outputs that are incomplete or se…
Evaluating Uncertainty Quantification Methods in Argumentative Large Language Models
Kevin Zhou, Adam Dejl, Gabriel Freedman +3
Research in uncertainty quantification (UQ) for large language models (LLMs) is increasingly important towards guaranteeing the reliability of this groundbreaking technology. We ex…
XAI-Units: Benchmarking Explainability Methods with Unit Tests
Jun Rui Lee, Sadegh Emami, Michael David Hollins +5
Feature attribution (FA) methods are widely used in explainable AI (XAI) to help users understand how the inputs of a machine learning model contribute to its outputs. However, dif…