14 citations · 65 across the 17 of their papers we have counts for
4 papers · 1 filter
Natural Language Inference Improves Compositionality in Vision-Language Models
Paola Cascante-Bonilla, Yu Hou, Yang Trista Cao +2
Compositional reasoning in Vision-Language Models (VLMs) remains challenging as these models often struggle to relate objects, attributes, and spatial relationships. Recent methods…
PropTest: Automatic Property Testing for Improved Visual Programming
Jaywon Koo, Ziyan Yang, Paola Cascante-Bonilla +2
Visual Programming has recently emerged as an alternative to end-to-end black-box visual reasoning models. This type of method leverages Large Language Models (LLMs) to generate th…
Learning from Synthetic Data for Visual Grounding
Ruozhen He, Ziyan Yang, Paola Cascante-Bonilla +2
This paper extensively investigates the effectiveness of synthetic training data to improve the capabilities of vision-and-language models for grounding textual descriptions to ima…
Grounding Language Models for Visual Entity Recognition
Zilin Xiao, Ming Gong, Paola Cascante-Bonilla +3
We introduce AutoVER, an Autoregressive model for Visual Entity Recognition. Our model extends an autoregressive Multi-modal Large Language Model by employing retrieval augmented c…