Papers with real-world human summaries

1 papers
Can Language Models Capture Human Writing Preferences for Domain-Specific Text Summarization? (2025.findings-acl)

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Challenge: Recent studies employ large language models as auxiliary tools for humancentered NLP.
Approach: They construct a model to capture human writing preferences by fine-tuning pre-trained models with data and designing prompts to optimize the output of large language models.
Outcome: The proposed model captures human writing preferences through the dimensions of length, content depth, tone & style, and summary format.

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