Unsupervised Extractive Summarization
18 papers with code • 3 benchmarks • 4 datasets
Pubmed
FacetSum
XWikiRef
Most implemented papers
Unsupervised Extractive Summarization-Based Representations for Accurate and Explainable Collaborative Filtering
reinaldncku/escofilt
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ACL 2021
Our explainability study demonstrates the superiority of and preference for summary-level explanations over other explanation types.
TWEETSUMM -- A Dialog Summarization Dataset for Customer Service
nlpyang/PreSumm
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In most cases, at the end of the conversation, agents are asked to write a short summary emphasizing the problem and the proposed solution, usually for the benefit of other agents that may have to deal with the same customer or issue.
On the Trade-off between Redundancy and Local Coherence in Summarization
Extractive summaries are usually presented as lists of sentences with no expected cohesion between them and with plenty of redundant information if not accounted for.
Computing and Exploiting Document Structure to Improve Unsupervised Extractive Summarization of Legal Case Decisions
Though many algorithms can be used to automatically summarize legal case decisions, most fail to incorporate domain knowledge about how important sentences in a legal decision relate to a representation of its document structure.
Improving Sentence Similarity Estimation for Unsupervised Extractive Summarization
Unsupervised extractive summarization aims to extract salient sentences from a document as the summary without labeled data.
XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages
But, for low-resource languages, the scarcity of reference articles makes monolingual summarization ineffective in solving this problem.
Unsupervised Extractive Summarization of Emotion Triggers
Second, we develop new unsupervised learning models that can jointly detect emotions and summarize their triggers.
Bipartite Graph Pre-training for Unsupervised Extractive Summarization with Graph Convolutional Auto-Encoders
opensum/bigae
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Pre-trained sentence representations are crucial for identifying significant sentences in unsupervised document extractive summarization.
