7 papers · 1 filter
ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding
Hangjie Yuan, Yichen Qian, Zhiwei Tang +21
Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric chall…
Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models
Jiazheng Xing, Hangjie Yuan, Lingling Cai +9
Connector-based video unified models have demonstrated strong capability in instruction-grounded video synthesis, but integrating a large high-fidelity generator into the unified t…
SpanVLA: Learning from Negative-Recovery Samples with Fast Action Bridging for Vision-Language-Action Model
Zewei Zhou, Ruining Yang, Xuewei Qi +9
Vision-Language-Action (VLA) models bring rich world knowledge and reasoning capabilities to autonomous driving. However, most driving VLAs are trained only on positive expert demo…
CoInteract: Physically-Consistent Human-Object Interaction Video Synthesis via Spatially-Structured Co-Generation
Xiangyang Luo, Xiaozhe Xin, Tao Feng +3
Synthesizing human--object interaction (HOI) videos has broad practical value in e-commerce, digital advertising, and virtual marketing. However, current diffusion models, despite…
CogFlow: Bridging Perception and Reasoning through Knowledge Internalization for Visual Mathematical Problem Solving
Shuhang Chen, Yunqiu Xu, Junjie Xie +7
Despite significant progress, multimodal large language models continue to struggle with visual mathematical problem solving. Some recent works recognize that visual perception is…
Lumos-1: On Autoregressive Video Generation with Discrete Diffusion from a Unified Model Perspective
Hangjie Yuan, Weihua Chen, Jun Cen +11
Autoregressive large language models (LLMs) have unified a vast range of language tasks, inspiring preliminary efforts in autoregressive (AR) video generation. Existing AR video ge…
MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems
Shuhang Chen, Hangjie Yuan, Yunqiu Xu +5
Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially in reliably perceiving and inte…