Papers by Arian Hosseini

1 papers
Understanding by Understanding Not: Modeling Negation in Language Models (2021.naacl-main)

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Challenge: Negation is a core construction in natural language, but state-of-the-art pre-trained language models often handle it incorrectly.
Approach: They propose to augment language modeling objective with unlikelihood objective based on negated generic sentences from a raw text corpus.
Outcome: The proposed approach reduces the top 1 error rate to 4% on negated LAMA dataset and improves on negating NLI benchmarks.

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