From the 1 of 31 linked papers with an AI index.
1 citations · 1 across the 21 of their papers we have counts for
8 papers · 1 filter
See2Think: Do Multimodal Models Really Use Intermediate Visual States?
Siyu Yan, Zhuoran Yan, Haiying Xu +10
The paper presents See2Think, an evaluation framework and benchmark for testing whether multimodal large language models actually use intermediate visual states during reasoning, a…
Are Text-to-Image Models Inductivist Turkeys? A Counterfactual Benchmark for Causal Reasoning
Jiayi Lei, Yuandong Pu, Xingyu Han +8
Text-to-image (T2I) generation models have achieved remarkable progress in producing visually realistic images from natural language prompts. Yet it remains unclear whether their s…
Faithful, Enriched, and Precise: Benchmarking Natural-Science Illustration Generation by T2I models
Yifan Chang, Jiaxin Ai, Jianwen Sun +9
Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts and processes. As Text-to-Ima…
Omni-Weather: A Unified Multimodal Model for Weather Radar Understanding and Generation
Zhiwang Zhou, Yuandong Pu, Xuming He +10
Weather modeling requires both accurate prediction and mechanistic interpretation, yet existing methods treat these goals in isolation, separating generation from understanding. To…
Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development
Zhongying Deng, Cheng Tang, Ziyan Huang +124
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…
Factuality Matters: When Image Generation and Editing Meet Structured Visuals
Le Zhuo, Songhao Han, Yuandong Pu +8
While modern visual generation models excel at creating aesthetically pleasing natural images, they struggle with producing or editing structured visuals like charts, diagrams, and…