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Improving Sentence Similarity Estimation for Unsupervised Extractive Summarization
Shichao Sun, Ruifeng Yuan, Wenjie Li +1
Unsupervised extractive summarization aims to extract salient sentences from a document as the summary without labeled data. Recent literatures mostly research how to leverage sent…
Few-shot Query-Focused Summarization with Prefix-Merging
Ruifeng Yuan, Zili Wang, Ziqiang Cao +1
Query-focused summarization has been considered as an important extension for text summarization. It aims to generate a concise highlight for a given query. Different from text sum…
Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT
Ruifeng Yuan, Zili Wang, Wenjie Li
Most current extractive summarization models generate summaries by selecting salient sentences. However, one of the problems with sentence-level extractive summarization is that th…
NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation
Hui Su, Xiaoyu Shen, Wenjie Li +1
Sequence-to-Sequence (seq2seq) models have become overwhelmingly popular in building end-to-end trainable dialogue systems. Though highly efficient in learning the backbone of huma…
Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach
Jingjing Xu, Xu Sun, Qi Zeng +4
The goal of sentiment-to-sentiment "translation" is to change the underlying sentiment of a sentence while keeping its content. The main challenge is the lack of parallel data. To…
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation
Shuming Ma, Xu Sun, Wei Li +3
Most recent approaches use the sequence-to-sequence model for paraphrase generation. The existing sequence-to-sequence model tends to memorize the words and the patterns in the tra…