2 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
Ovis-Image Technical Report
Guo-Hua Wang, Liangfu Cao, Tianyu Cui +8
We introduce , a 7B text-to-image model specifically optimized for high-quality text rendering, designed to operate efficiently under stringent computational c…
Hierarchical Semantic Tree Anchoring for CLIP-Based Class-Incremental Learning
Tao Hu, Lan Li, Zhen-Hao Xie +1
Class-Incremental Learning (CIL) enables models to learn new classes continually while preserving past knowledge. Recently, vision-language models like CLIP offer transferable feat…
BOFA: Bridge-Layer Orthogonal Low-Rank Fusion for CLIP-Based Class-Incremental Learning
Lan Li, Tao Hu, Da-Wei Zhou +3
Class-Incremental Learning (CIL) aims to continually learn new categories without forgetting previously acquired knowledge. Vision-language models such as CLIP offer strong transfe…
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye +1
Domain-Incremental Learning (DIL) focuses on continual learning in non-stationary environments, requiring models to adjust to evolving domains while preserving historical knowledge…
UniCA: Unified Covariate Adaptation for Time Series Foundation Model
Lu Han, Yu Liu, Lan Li +9
Time Series Foundation Models (TSFMs) have achieved remarkable success through large-scale pretraining. However, their design primarily targets real-valued series, limiting their a…