Papers with unsupervised summarization framework

2 papers
RTSUM: Relation Triple-based Interpretable Summarization with Multi-level Salience Visualization (2024.naacl-demo)

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Challenge: Abstractive summarization has emerged as a critical tool in the era of information overload.
Approach: They propose an unsupervised summarization framework that utilizes relation triples as the basic unit for summarizing.
Outcome: The proposed framework visualizes salience levels for sentences, relation triples, and phrases.
Multi-TimeLine Summarization (MTLS): Improving Timeline Summarization by Generating Multiple Summaries (2021.acl-long)

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Challenge: Existing work on Time-Line Summarization (TLS) has focused on improving the performance of summarization but its drawbacks are as follows: a homogeneous dataset makes it hard to generalize; output is usually a single timeline regardless of the size and complexity of the input dataset.
Approach: They propose a task that generates a time-line for each story given a news article . they propose MTLS task that can be generalized to other news articles .
Outcome: The proposed task can generate bet-ter results than Time-Line Summarization (TLS) the proposed task is based on previous evaluation methods.

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