AI Research
How Many Examples, and Which Ones? A Study of In-Context Learning for Natural Language Inference
A study examines example quantity and selection in in-context learning for natural language inference.
Natural language inference (NLI) is a fundamental task of natural language processing and crucial for evaluating the strengths and weaknesses of AI methods.
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ArXiv CS.CL
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ArXiv CS.CL
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The study focuses on how the number and selection of examples affect in-context learning for natural language inference. Understanding these choices matters because NLI is used to assess AI methods’ strengths and weaknesses.
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