ReMask：域反事实生成的鲁棒信息遮盖方法（英文版）

英文标题：ReMask: A Robust Information-Masking Approach for Domain Counterfactual Generation中文摘要：本文提出了一种三步域混淆方法，通过基于频率和注意力规范的掩盖来遮蔽特定于域的线索，并揭示域泛化上下文，从而实现了领域反事实样本的生成，通过实验验证本方法在领域情感分类、对抗领域适应和多领域意图分类任务中的有效性。英文摘要：Domain shift is a big challenge in NLP, thus, many approaches resort tolearning domain-invariant features to mitigate the inference phase domainshift. Such methods, however, fail to leverage the domain-specific nuancesrelevant to the task at hand. To avoid such drawbacks, domain counterfactualge