4 papers · 1 filter
Stage-adaptive Token Selection for Efficient Omni-modal LLMs
Zijie Xin, Jie Yang, Ruixiang Zhao +4
The unified audio-visual understanding capability of omni-modal large language models (om-LLMs) comes at the high cost of processing tens of thousands of visual and audio tokens th…
OmniPro: A Comprehensive Benchmark for Omni-Proactive Streaming Video Understanding
Ruixiang Zhao, Jie Yang, Zijie Xin +4
Omni-proactive streaming video understanding, i.e., autonomously deciding when to speak and what to say from continuous audio-visual streams, is an emerging capability of omni-moda…
Fundus-R1: Training a Fundus-Reading MLLM on Public Data
Yuchuan Deng, Qijie Wei, Kaiheng Qian +8
Fundus imaging such as CFP, OCT and UWF is crucial for the early detection of retinal anomalies and diseases. Fundus image understanding, due to its knowledge-intensive nature, pos…
SAVE: Speech-Aware Video Representation Learning for Video-Text Retrieval
Ruixiang Zhao, Zhihao Xu, Bangxiang Lan +3
For video-text retrieval, the use of CLIP has been a de facto choice. Since CLIP provides only image and text encoders, this consensus has led to a biased paradigm that entirely ig…