4 papers
Hyperbolic and Evidence-Prioritized Experts for Large Vision-Language Models
Zijie Zhou, Dandan Zhu, Hangxiangpan Wang +3
Large Vision-Language Models (LVLMs) have demonstrated impressive performance on multimodal tasks through scaled architectures and extensive training. Recent studies introduce Mixt…
CardioLens: Revealing the Clinical Reality Gap of MLLMs via Multi-Sequence Cardiac MRI Evaluations
Zixian Su, Hongkai Zhang, Fan Gao +12
Multimodal Large Language Models (MLLMs) have shown strong performance on public medical benchmarks, yet existing evaluations often remain weak proxies for clinical use, relying on…
Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Team Seedance, Heyi Chen, Siyan Chen +194
Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Yu Gao, Haoyuan Guo, Tuyen Hoang +41
Notable breakthroughs in diffusion modeling have propelled rapid improvements in video generation, yet current foundational model still face critical challenges in simultaneously b…