NettetOur method learns to dynamically prompt (L2P) a pre-trained model to learn tasks sequentially under different task transitions. In our proposed framework, prompts are small learnable parameters, which are maintained in a memory space. The objective is to optimize prompts to instruct the model prediction and explicitly manage task-invariant … Nettet基于这个思想，我们再一次将Prompt升华到更高的层面—— Prompt的本质是参数有效性学习（Parameter-Efficient Learning，PEL） 。 参数有效性学习的背景 ：在一般的计算资源条件下，大规模的模型（例如GPT-3）很难再进行微调，因为所有的参数都需要计算梯度并进行更新，消耗时间和空间资源。

GitHub - JH-LEE-KR/l2p-pytorch: Pytorch Implementation of Learning …

Nettet1. jun. 2024 · Further, key-value methods are particularly strong in continual learning settings, with recent works demonstrating prompt-learning for NLP [33, 34] for applications like text retrieval [35]. Nettet26. jun. 2024 · Dataset for continual learning. where (x, y) is the image and label pairs. The labels are mutually exclusive across different training sets. When learning on a given session S, we only have access ... hesse automaker

CVPR 2024 Open Access Repository

NettetPrompt将学习下游任务从直接调整模型权重改为设计提示“指导”模型有条件地执行任务。提示编码特定于任务的知识，比普通微调更有效地利用预训练的冻结模型。 prompt learning：可以使基于序列的模型具有更高的学习特征的能力. instance-wise：样例水平 NettetOur method learns to dynamically prompt (L2P) a pre-trained model to learn tasks sequentially under different task transitions. In our proposed framework, prompts are … Nettet24. jun. 2024 · Our method learns to dynamically prompt (L2P) a pre-trained model to learn tasks sequen-tially under different task transitions. In our proposed framework, prompts are small learnable parameters, which are maintained in a memory space. The objective is to optimize prompts to instruct the model prediction and ex-plicitly manage … hesselkamp