Papers with output personalization

1 papers
Personalized Abstractive Summarization by Tri-agent Generation Pipeline (2024.findings-eacl)

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Challenge: Existing research shows that large language models do not consistently satisfy users' preferences or expectations.
Approach: They propose a tri-agent generation pipeline that includes a generator, an instructor, and an editor to enhance output personalization.
Outcome: The proposed pipeline generates outputs that better meet user expectations on two abstractive summarization datasets.

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