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Research questionHow can conformal prediction preserve coverage while removing irrelevant content from NLP document extracts?Document selection for language tasks must retain enough pertinent information for the task while excluding irrelevant material. Designing relevance scores that make this tradeoff reliably across tasks is difficult without hand-crafted prompts for each one.
Information Retrieval
Machine Learning
Natural Language Processing
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Unifying Conformal Language Tasks with In-Context EnsemblesThe source addresses conformal prediction for summarization, extractive question answering, and five other NLP tasks. It studies in-context ensemble relevance scoring, with theoretical analysis of ensemble diversity and reported results across seven tasks.research paper · Sep 2, 2026
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