Incentivizing Temporal-Awareness in Egocentric Video Understanding Models
Researchers have introduced TimeThink, a new framework designed to help video large language models better process temporal information in long-form recordings. The system improves accuracy by identifying and verifying specific moments within a video sequence, addressing a common weakness in existing models that struggle to maintain context over time.
Covered by 2 sources · 7 articles
- AApple Machine Learning Blog↗22h ago
- AarXiv CS.AI↗Harsh Goel, S P Sharan, Sahil Shah, Minkyu Choi, Joungbin An, Kristen Grauman, Sandeep P. Chinchali2d ago
- AarXiv CS.AI↗Baolu Li (Victor), Jingyu Qian (Victor), Rui Guo (Victor), Yilun Chen (Victor), Hanpeng Liu (Victor), Yuan Lin (Victor), Junhong Zhou (Victor), Ruixin Liu (Victor), Liu Yang (Victor), Yutong Zheng (Victor), Zhenli Zhang (Victor), Sean Li (Victor), Chaoda Zheng (Victor), Boyang Wang (Victor), Tenglong (Victor), Gu, Zhuangzhuang Ding, Pengkun Zheng, Yu Zhang, Xianming Liu18h ago
- AarXiv CS.AI↗Youngkil Song, Yoonjae Baek, Dongwon Kim, Inho Kim, Dongkeun Kim, Suha Kwak2d ago
- AarXiv CS.AI↗Handong Li, Longteng Guo, Zikang Liu, Dongze Hao, Yepeng Tang, Zijia Zhao, Jie Jiang, Zhiwei Jin, Chen Chen, Haonan Lu, Jing Liu2d ago
- AarXiv CS.AI↗Yibin Liu, Yaxing Lyu, Daqi Gao, Zhixuan Liang, Weiliang Tang, Shilong Mu, Xiaokang Yang, Yao Mu1d ago
- AarXiv CS.AI↗Zhenkun Gao, Yicheng Bao, Jinlong Peng, Xueheng Li, Theo Huang, Bangwei Liu, Kunquan Li, Zhenye Gan, Tao Hu, Chengjun Xie, Mingqian Yang, Xuanhua He, Zhizhong Zhang, Xin Tan, Chengjie Wang, Yuan Xie2d ago