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Assessing and Learning Alignment of Unimodal Vision and Language Models
Le Zhang, Qian Yang, Aishwarya Agrawal
How well are unimodal vision and language models aligned? Although prior work have approached answering this question, their assessment methods do not directly translate to how the…
VisMin: Visual Minimal-Change Understanding
Rabiul Awal, Saba Ahmadi, Le Zhang +1
Fine-grained understanding of objects, attributes, and relationships between objects is crucial for visual-language models (VLMs). Existing benchmarks primarily focus on evaluating…
Benchmarking Vision Language Models for Cultural Understanding
Shravan Nayak, Kanishk Jain, Rabiul Awal +5
Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their…
Decompose and Compare Consistency: Measuring VLMs' Answer Reliability via Task-Decomposition Consistency Comparison
Qian Yang, Weixiang Yan, Aishwarya Agrawal
Despite tremendous advancements, current state-of-the-art Vision-Language Models (VLMs) are still far from perfect. They tend to hallucinate and may generate biased responses. In s…
An Introduction to Vision-Language Modeling
Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay +38
Following the recent popularity of Large Language Models (LLMs), several attempts have been made to extend them to the visual domain. From having a visual assistant that could guid…
Improving Text-to-Image Consistency via Automatic Prompt Optimization
Oscar Mañas, Pietro Astolfi, Melissa Hall +6
Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic im…