Papers with negation sensitivity

1 papers
Revisiting subword tokenization: A case study on affixal negation in large language models (2024.naacl-long)

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Challenge: Negation is central to language understanding but is not properly captured by modern NLP methods.
Approach: They propose to use subword tokenization methods to detect negation in large language models . they find that models can reliably recognize negation, despite mismatches in tokenization accuracy .
Outcome: The proposed models can detect negation in English using subword tokenization methods despite some mismatches in tokenization accuracy and negation detection performance.

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