BriefGPT.xyz
Oct, 2023
通过逐层维度选择从预训练语言模型中解析单词语义
Breaking Down Word Semantics from Pre-trained Language Models through Layer-wise Dimension Selection
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Nayoung Choi
TL;DR
该论文使用二进制掩码对预训练模型中不同层的输出进行切割,以解离BERT中的语义意义,而不更新预训练参数,从而产生解离的嵌入表示。使用二进制分类验证解离的嵌入的效果,判断两个不同句子中目标词的含义是否相同。实验结果表明,利用层次信息是有效的,而解离的语义意义进一步提高了性能。
Abstract
contextual word embeddings
obtained from
pre-trained language model
(PLM) have proven effective for various natural language processing tasks at the word level. However, interpreting the hidden aspects within emb
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