1.2k citations · 1.8k across the 35 of their papers we have counts for
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ViUniT: Visual Unit Tests for More Robust Visual Programming
Artemis Panagopoulou, Honglu Zhou, Silvio Savarese +4
Programming based approaches to reasoning tasks have substantially expanded the types of questions models can answer about visual scenes. Yet on benchmark visual reasoning data, wh…
Contextualized Evaluations: Judging Language Model Responses to Underspecified Queries
Chaitanya Malaviya, Joseph Chee Chang, Dan Roth +3
Language model users often issue queries that lack specification, where the context under which a query was issued -- such as the user's identity, the query's intent, and the crite…
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models
Matt Deitke, Christopher Clark, Sangho Lee +47
Today's most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good perfor…
LLM-based Hierarchical Concept Decomposition for Interpretable Fine-Grained Image Classification
Renyi Qu, Mark Yatskar
(Renyi Qu's Master's Thesis) Recent advancements in interpretable models for vision-language tasks have achieved competitive performance; however, their interpretability often suff…
A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
Yue Yang, Mona Gandhi, Yufei Wang +5
While deep networks have achieved broad success in analyzing natural images, when applied to medical scans, they often fail in unexcepted situations. We investigate this challenge…
DOLOMITES: Domain-Specific Long-Form Methodical Tasks
Chaitanya Malaviya, Priyanka Agrawal, Kuzman Ganchev +7
Experts in various fields routinely perform methodical writing tasks to plan, organize, and report their work. From a clinician writing a differential diagnosis for a patient, to a…