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cs.CL2023
Retrieval-Augmented Classification with Decoupled Representation
Xinnian Liang, Shuangzhi Wu, Hui Huang +3
Retrieval augmented methods have shown promising results in various classification tasks. However, existing methods focus on retrieving extra context to enrich the input, which is…
cs.CL2023★ 2 cited
Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models
Xinnian Liang, Zefan Zhou, Hui Huang +5
Pretrained language models (PLMs) have shown marvelous improvements across various NLP tasks. Most Chinese PLMs simply treat an input text as a sequence of characters, and complete…
cs.CL2023
Enhancing Dialogue Summarization with Topic-Aware Global- and Local- Level Centrality
Xinnian Liang, Shuangzhi Wu, Chenhao Cui +3
Dialogue summarization aims to condense a given dialogue into a simple and focused summary text. Typically, both the roles' viewpoints and conversational topics change in the dialo…