Papers by Tikka Arjun Singh Bedi

1 papers
Humans Hallucinate Too: Language Models Identify and Correct Subjective Annotation Errors With Label-in-a-Haystack Prompts (2025.emnlp-main)

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Challenge: Existing approaches to model complex subjective tasks in natural language are limited by significant variation in annotations.
Approach: They propose a simple in-context learning binary filtering baseline that estimates the reasonableness of a document-label pair.
Outcome: The proposed approach can be integrated into annotation pipelines to enhance signal-to-noise ratios.

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