Papers with text-to-text language model

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.
Dialogue Summaries as Dialogue States (DS2), Template-Guided Summarization for Few-shot Dialogue State Tracking (2022.findings-acl)

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Challenge: Annotating task-oriented dialogues is notorious for the expensive and difficult data collection process.
Approach: They propose to reformulate dialogue state tracking as a dialogue summarization problem by using synthetic dialogue summaries generated by a set of rules.
Outcome: The proposed method outperforms previous studies on few-shot dialogue state tracking in MultiWoZ 2.0 and 2.1 in cross-domain and multi-domain settings.

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