1 citations · 1 across the 3 of their papers we have counts for
3 papers
ALOHa: A New Measure for Hallucination in Captioning Models
Suzanne Petryk, David M. Chan, Anish Kachinthaya +4
Despite recent advances in multimodal pre-training for visual description, state-of-the-art models still produce captions containing errors, such as hallucinating objects not prese…
CLAIR: Evaluating Image Captions with Large Language Models
David Chan, Suzanne Petryk, Joseph E. Gonzalez +2
The evaluation of machine-generated image captions poses an interesting yet persistent challenge. Effective evaluation measures must consider numerous dimensions of similarity, inc…
Simple Token-Level Confidence Improves Caption Correctness
Suzanne Petryk, Spencer Whitehead, Joseph E. Gonzalez +3
The ability to judge whether a caption correctly describes an image is a critical part of vision-language understanding. However, state-of-the-art models often misinterpret the cor…