5 papers
KeepLoRA: Continual Learning with Residual Gradient Adaptation
Mao-Lin Luo, Zi-Hao Zhou, Yi-Lin Zhang +3
Continual learning for pre-trained vision-language models requires balancing three competing objectives: retaining pre-trained knowledge, preserving knowledge from a sequence of le…
LADA: Scalable Label-Specific CLIP Adapter for Continual Learning
Mao-Lin Luo, Zi-Hao Zhou, Tong Wei +1
Continual learning with vision-language models like CLIP offers a pathway toward scalable machine learning systems by leveraging its transferable representations. Existing CLIP-bas…
Weakly-Supervised Contrastive Learning for Imprecise Class Labels
Zi-Hao Zhou, Jun-Jie Wang, Tong Wei +1
Contrastive learning has achieved remarkable success in learning effective representations, with supervised contrastive learning often outperforming self-supervised approaches. How…
Personalized Federated Learning via Learning Dynamic Graphs
Ziran Zhou, Guanyu Gao, Xiaohu Wu +1
Personalized Federated Learning (PFL) aims to train a personalized model for each client that is tailored to its local data distribution, learning fails to perform well on individu…
2-Tier SimCSE: Elevating BERT for Robust Sentence Embeddings
Yumeng Wang, Ziran Zhou, Junjin Wang
Effective sentence embeddings that capture semantic nuances and generalize well across diverse contexts are crucial for natural language processing tasks. We address this challenge…