Continual Skill and Task Learning via Dialogue visual-motor control policy ACT with Low Rank Adaptation (ACT-LoRA), which enables the existing SoTA ACT model to perform few-shot continual learning. Se... W Gu,S Kondepudi,L Huang,... 被引量: 0发表: 2024年 Adaptive Rank, Reduced Forgettin...
Continual learning (CL) aims to help deepneural networksto learn new knowledge while retaining what has been learned. Recently, pre-trained vision-language models such as CLIP, with powerful generalization ability, have been gaining traction as practical CL candidates. However, the domain mismatch be...
DT offers advantages in learning efficiency, distribution shift mitigation, and zero-shot generalization but exacerbates the forgetting problem during supervised parameter updates. We introduce multi-head DT (MH-DT) and low-rank adaptation DT (LoRA-DT) to mitigate DT's forgetting problem. MH-DT ...
S-LoRA: Scalable Low-Rank Adaptation for Class Incremental Learning 2025 ICLR Spurious Forgetting in Continual Learning of Language Models 2025 ICLR PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning) 2025 AAAI MOS: Model Surgery for Pre-Trained Mod...
1) Learning: the pre-trained model adapts to the new task by tuning an online PET mod- ule, along with our adaptation speed calibration to align different PET modules, 2) Accumulation: the task-specific knowledge learned by the online PET module is ac...
Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685, 2021. 3 [19] Zixuan Ke, Bing Liu, and Xingchang Huang. Continual learning of a mixed sequence of similar and dissimilar tasks. NeurIPS, 33, 2020. 1, 3, 5 [20] Diederik P Kingma and Jimmy Ba. Adam...
Hu, E.J., et al.: LoRa: low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021) Ke, Z., Liu, B., Huang, X.: Continual learning of a mixed sequence of similar and dissimilar tasks. In: NeurIPS 33 (2020) Google Scholar Kingma, D.P., Ba, J.: Ada...
S-LoRA: Scalable Low-Rank Adaptation for Class Incremental Learning no code yet • 22 Jan 2025 Continual Learning (CL) with foundation models has recently emerged as a promising approach to harnessing the power of pre-trained models for sequential tasks....
Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation [MICCAI 2024] [paper] Federated Cross-Incremental Self-Supervised Learning for Medical Image Segmentation [TNNLS 2024] [paper] CLMS: Bridging Domain Gaps in Medical Imaging Segm...
Table 1. Non-IID learning scenarios in Federated Learning, and the strategies that could potentially solve each situation. Strategies that deal with changes in both the input space and the behaviour are placed only in the last column, and not in the previous ones. 3.2. State-of-the-art clas...