1 citations · 1 across the 12 of their papers we have counts for
12 papers
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…
Towards Error-Free Long Video Generation
Shuning Chang, Weihua Chen, Jiasheng Tang +8
Recent advances in video generation have made minute-level synthesis possible; however, generating long videos remains challenging due to error accumulation, attribute drift, and t…
ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning
Sicheng Yang, Hangjie Yuan, Wenjun Zhang +5
Building trustworthy medical multimodal large language models (MLLMs) is critical for reliable clinical decision support. Existing medical hallucination benchmarks mainly focus on…
Towards 3D-Aware Video Diffusion Models: Render-Free Human Motion Control with Mesh Tokenization
Jingyun Liang, Min Wei, Shikai Li +5
Diffusion models have shown remarkable success in video generation. However, whether such models are truly aware of the 3D structure underlying visual observations, rather than sim…
Knowledge is Power: Advancing Few-shot Action Recognition with Multimodal Semantics from MLLMs
Jiazheng Xing, Chao Xu, Hangjie Yuan +4
Multimodal Large Language Models (MLLMs) have propelled the field of few-shot action recognition (FSAR). However, preliminary explorations in this area primarily focus on generatin…
MCIE: Multimodal LLM-Driven Complex Instruction Image Editing with Spatial Guidance
Xuehai Bai, Xiaoling Gu, Akide Liu +3
Recent advances in instruction-based image editing have shown remarkable progress. However, existing methods remain limited to relatively simple editing operations, hindering real-…
A-LLM: An End-to-end Conversational Audio Avatar Large Language Model
Xiaolin Hu, Hang Yuan, Xinzhu Sang +4
Developing expressive and responsive conversational digital humans is a cornerstone of next-generation human-computer interaction. While large language models (LLMs) have significa…
RynnVLA-002: A Unified Vision-Language-Action and World Model
Jun Cen, Siteng Huang, Yuqian Yuan +11
We introduce RynnVLA-002, a unified Vision-Language-Action (VLA) and world model. The world model leverages action and visual inputs to predict future image states, learning the un…
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…
WorldVLA: Towards Autoregressive Action World Model
Jun Cen, Chaohui Yu, Hangjie Yuan +9
We present WorldVLA, an autoregressive action world model that unifies action and image understanding and generation. Our WorldVLA intergrates Vision-Language-Action (VLA) model an…
VideoMAR: Autoregressive Video Generatio with Continuous Tokens
Hu Yu, Biao Gong, Hangjie Yuan +5
Masked-based autoregressive models have demonstrated promising image generation capability in continuous space. However, their potential for video generation remains under-explored…
Frequency Autoregressive Image Generation with Continuous Tokens
Hu Yu, Hao Luo, Hangjie Yuan +3
Autoregressive (AR) models for image generation typically adopt a two-stage paradigm of vector quantization and raster-scan ``next-token prediction", inspired by its great success…