Papers by Simone Teglia

1 papers
How Much Do Encoder Models Know About Word Senses? (2025.acl-long)

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Challenge: Word Sense Disambiguation (WSD) is a key task in Natural Language Processing (NLP) however, how well these models inherently disambiguate word senses remains uncertain.
Approach: They evaluate several encoder-only PLMs across WordNet and ODE sense inventories to evaluate their ability to separate word senses without any task-specific fine-tuning.
Outcome: The proposed model outperforms output layer on WordNet and ODE sense inventories by 15 percentage points.

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