43 citations · 150 across the 26 of their papers we have counts for
6 papers · 1 filter
Self-Evolving Code-with-Image Reasoning
Tianze Yang, Liang Wu, Ruitong Sun +6
Multimodal models increasingly reach for tools when solving visual tasks (crop, zoom, rotate, brighten), a paradigm known as thinking-with-images. The central challenge is one of p…
Self-Improving Small Object Grounding in LVLMs
Tianze Yang, Yucheng Shi, Ruitong Sun +2
Can internal attention patterns in Large Vision Language Models (LVLMs) identify reliable small-object boxes without fine-tuning? In this work, we provide an affirmative answer. At…
RadFabric: Agentic AI System with Reasoning Capability for Radiology
Wenting Chen, Yi Dong, Zhaojun Ding +14
Chest X ray (CXR) imaging remains a critical diagnostic tool for thoracic conditions, but current automated systems face limitations in pathology coverage, diagnostic accuracy, and…
Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data
Yucheng Shi, Quanzheng Li, Jin Sun +2
Large Multimodal Models (LMMs), or Vision-Language Models (VLMs), have shown impressive capabilities in a wide range of visual tasks. However, they often struggle with fine-grained…
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications
Chenjiao Tan, Qian Cao, Yiwei Li +15
The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabi…
Automated Natural Language Explanation of Deep Visual Neurons with Large Models
Chenxu Zhao, Wei Qian, Yucheng Shi +2
Deep neural networks have exhibited remarkable performance across a wide range of real-world tasks. However, comprehending the underlying reasons for their effectiveness remains a…