7 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
Haoyuan Li, Qihang Cao, Tao Tang +6
Recent progress in spatial reasoning with Multimodal Large Language Models (MLLMs) increasingly leverages geometric priors from 3D encoders. However, most existing integration stra…
Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
Songtao Jiang, Yuan Wang, Sibo Song +22
Real-world clinical decision-making requires integrating heterogeneous data, including medical text, 2D images, 3D volumes, and videos, while existing AI systems fail to unify all…
Causal-SAM-LLM: Large Language Models as Causal Reasoners for Robust Medical Segmentation
Tao Tang, Shijie Xu, Jionglong Su +1
The clinical utility of deep learning models for medical image segmentation is severely constrained by their inability to generalize to unseen domains. This failure is often rooted…
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs
Haoyuan Li, Yanpeng Zhou, Yufei Gao +7
Remarkable progress in 2D Vision-Language Models (VLMs) has spurred interest in extending them to 3D settings for tasks like 3D Question Answering, Dense Captioning, and Visual Gro…
UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting
Haoyuan Li, Yanpeng Zhou, Tao Tang +5
Recent advancements in multi-modal 3D pre-training methods have shown promising efficacy in learning joint representations of text, images, and point clouds. However, adopting poin…
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…