← Search

Hongcheng Li

2 accepted papers

2025

Adapt and Feature Translation for Class-Incremental Learning with Pre-Trained Models

ICASSP 2025accepted

Class-incremental learning (CIL) aims to enable a learning system to continuously learn new information. Although pre-trained models (PTMs) exhibit strong performance in CIL, the lack of data from previously learned classes results in class imbalance and catastrophic forgetting during the updating p…

Cited by 0Source ↗Scholar ↗
2025

Diversity-Enhanced Distribution Alignment for Dataset Distillation

ICCV 2025poster

Dataset distillation, which compresses large-scale datasets into compact synthetic representations (i.e., distilled datasets), has become crucial for the efficient training of modern deep learning architectures. While existing large-scale dataset distillation methods leverage a pre-trained model thr…

Cited by 0Source ↗PDF ↗Scholar ↗