G-MAP: General Memory-Augmented Pre-trained Language Model for Domain Tasks

• URL: http://arxiv.org/abs/2212.03613v3
• Date: Sat, 17 Feb 2024 19:31:47 GMT
• Title: G-MAP: General Memory-Augmented Pre-trained Language Model for Domain Tasks
• Authors: Zhongwei Wan, Yichun Yin, Wei Zhang, Jiaxin Shi, Lifeng Shang, Guangyong Chen, Xin Jiang, Qun Liu
• Abstract summary: We propose a new framework of General Memory Augmented Pre-trained Language Model (G-MAP) G-MAP augments the domain-specific PLM by a memory representation built from the frozen general PLM without losing any general knowledge. We demonstrate the effectiveness of G-MAP on various domains (biomedical and computer science publications, news, and reviews) and different kinds (text classification, QA, NER) of tasks.
• Score: 68.87524746922263
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recently, domain-specific PLMs have been proposed to boost the task performance of specific domains (e.g., biomedical and computer science) by continuing to pre-train general PLMs with domain-specific corpora. However, this Domain-Adaptive Pre-Training (DAPT; Gururangan et al. (2020)) tends to forget the previous general knowledge acquired by general PLMs, which leads to a catastrophic forgetting phenomenon and sub-optimal performance. To alleviate this problem, we propose a new framework of General Memory Augmented Pre-trained Language Model (G-MAP), which augments the domain-specific PLM by a memory representation built from the frozen general PLM without losing any general knowledge. Specifically, we propose a new memory-augmented layer, and based on it, different augmented strategies are explored to build the memory representation and then adaptively fuse it into the domain-specific PLM. We demonstrate the effectiveness of G-MAP on various domains (biomedical and computer science publications, news, and reviews) and different kinds (text classification, QA, NER) of tasks, and the extensive results show that the proposed G-MAP can achieve SOTA results on all tasks.

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