5 papers indexed
Gong Sitong, Tianyu Yan, Caixin Kang, Bo Zheng, Xiang Ruan, Huchuan Lu, et al.
When should an intelligent assistant speak up without being asked? Continuous egocentric video offers rich, evolving context that enables a new form of assistance: one that is proactive rather than merely reactive. Yet existing approaches either wait passively for user queries or…
Yuhao Wang, Mu Qiao, Haiwen Diao, Yunzhi Zhuge, Pingping Zhang, Xindong Zhang, et al.
Multimodal Large Language Models (MLLMs) incur prohibitive inference costs due to long visual token sequences. Training-free visual token reduction provides an efficient solution. However, existing methods distort attention distributions, giving rise to a phenomenon we term Atten…
Jialong Zhong, Tingwei Liu, Baokun Yue, Jingjing Li, Yongri Piao, Miao Zhang, et al.
Multimodal survival analysis utilizing whole slide images (WSIs) and genomic profiles is fundamental for cancer prognosis. Recently, state-space models like Mamba have emerged as powerful tools for sequence modeling. However, translating this success to complex multimodal tasks i…
Jian Shi, Cheng Zhen, Pingping Zhang, Rui Xu, Yanan Lv, Yili Ma, et al.
Language-guided Medical Image Segmentation (LMIS) has shown great potential to improve the delineation of anatomical structures and lesions by integrating clinical textual information. Existing methods generally rely on either implicit interaction between textual and visual featu…
Xiaomin Li, Qian Liang, Yinan Li, Ying Zhang, Chen Li, Jing Lyu, et al.
Reinforcement Learning like Group Relative Policy Optimization (GRPO) has significantly advanced text-to-image post-training. However, current methods often favor superficial aesthetics, such as over-saturated colors, leaving critical flaws like AI artifacts and biological implau…