2 citations · 3 across the 9 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.LG2026
Batch Loss Score for Dynamic Data Pruning
Qing Zhou, Bingxuan Zhao, Tao Yang +3
Dynamic data pruning accelerates deep learning by selectively omitting less informative samples during training. While per-sample loss is a common importance metric, obtaining it c…
cs.CV2026
Efficient Reasoning via Thought Compression for Language Segmentation
Qing Zhou, Shiyu Zhang, Yuyu Jia +4
Chain-of-thought (CoT) reasoning has significantly improved the performance of large multimodal models in language-guided segmentation, yet its prohibitive computational cost, stem…
cs.CV2026
One-Shot Crowd Counting With Density Guidance For Scene Adaptation
Jiwei Chen, Qi Wang, Junyu Gao +3
Crowd scenes captured by cameras at different locations vary greatly, and existing crowd models have limited generalization for unseen surveillance scenes. To improve the generaliz…