352 citations · 690 across the 42 of their papers we have counts for
6 papers · 1 filter
Benchmarking Foundation and Large Language Models for Few-Shot Medical Image Segmentation
Jinghong Liu, Yuchuan Deng, Fanping Liu +2
Few-shot medical image segmentation (FS-MIS) aims to segment novel regions of interest (ROIs) from a few annotated support examples. Despite rapid progress, existing FS-MIS solutio…
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…
Early Intervention for VFM-based Multimodal Medical Image Classification
Qijie Wei, Hailan Lin, Xirong Li
Current methods for multimodal medical image classification (M3IC) face two major challenges. First, the prevailing "fusion after unimodal image embedding" paradigm cannot fully ex…
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…