May 21, 2024, 4:44 a.m. | Junhao Zheng, Shengjie Qiu, Qianli Ma

cs.LG updates on

arXiv:2312.07887v2 Announce Type: replace-cross
Abstract: Incremental Learning (IL) has been a long-standing problem in both vision and Natural Language Processing (NLP) communities. In recent years, as Pre-trained Language Models (PLMs) have achieved remarkable progress in various NLP downstream tasks, utilizing PLMs as backbones has become a common practice in recent research of IL in NLP. Most assume that catastrophic forgetting is the biggest obstacle to achieving superior IL performance and propose various techniques to overcome this issue. However, we find …

arxiv cs.lg incremental incremental learning language language models learn recall replace type

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