Papers by Kai-Uwe Kühnberger

1 papers
FOOL ME IF YOU CAN! An Adversarial Dataset to Investigate the Robustness of LMs in Word Sense Disambiguation (2024.emnlp-main)

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Challenge: Word sense disambiguation (WSD) is a key task in natural language processing . however, these models struggle with recognizing semantic boundaries in adversarial contexts .
Approach: They propose to use a coarse-grained WSD dataset to assess model robustness . they found that some models struggled to correctly disambiguate homonyms in adversarial contexts .
Outcome: The proposed dataset includes four test sets to assess the robustness of language models in WSD tasks.

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