4 papers
Dynamic LoRA-Experts and Prototype-Ensemble Matching for Class-Incremental Learning
Hongwei Zhao, Rui Liu, Yansong Liu
Class-Incremental Learning (CIL) aims to continuously learn new classes without forgetting previously acquired knowledge. Parameter-efficient fine-tuning with pre-trained models re…
Hyperbolic Prototype Routing for Rehearsal-Free Class-Incremental Learning
HongWei Zhao, Rui Liu, Yong Chen
Class-Incremental Learning (CIL) aims to continually learn new classes while preserving prior knowledge. Parameter-efficient fine-tuning with pre-trained models enables CIL with mi…
Decoupled and Distilled: Task-Adaptive LoRA-Teachers with Ensemble Knowledge Transfer for Few-Shot Class-Incremental Learning
Hongwei Zhao, Rui Liu, Yansong Liu +2
Few-Shot Class-Incremental Learning (FSCIL) addresses the challenge of learning new classes from very limited samples while retaining knowledge of previously learned ones. Although…
HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation
Yansong Liu, Rui Liu, Yuan Zuo +6
Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early prefix of the timeline and the…