3 citations · 8 across the 13 of their papers we have counts for
3 papers · 1 filter
Discovering Divergent Representations between Text-to-Image Models
Lisa Dunlap, Joseph E. Gonzalez, Trevor Darrell +3
In this paper, we investigate when and how visual representations learned by two different generative models diverge. Given two text-to-image models, our goal is to discover visual…
Search Arena: Analyzing Search-Augmented LLMs
Mihran Miroyan, Tsung-Han Wu, Logan King +8
Search-augmented language models combine web search with Large Language Models (LLMs) to improve response groundedness and freshness. However, analyzing these systems remains chall…
Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling
Tsung-Han Wu, Heekyung Lee, Jiaxin Ge +3
Vision-Language Models (VLMs) excel at visual understanding but often suffer from visual hallucinations, where they generate descriptions of nonexistent objects, actions, or concep…