Papers by Jacob Hoffman

2 papers
MWE as WSD: Solving Multiword Expression Identification with Word Sense Disambiguation (2023.findings-emnlp)

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Challenge: Recent approaches to word sense disambiguation use encodings of the sense gloss and context information to improve performance.
Approach: They propose a poly-encoder architecture which uses the sense gloss to improve WSD performance.
Outcome: The proposed approach outperforms the state-of-the-art in word sense disambiguation by 1.9 F1 points and on the PARSEME 1.1 English dataset.
CoAM: Corpus of All-Type Multiword Expressions (2025.acl-long)

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Challenge: Existing datasets for multiword expressions are inconsistently annotated, limited to a single type of MWE, or limited in size.
Approach: They propose to use a new interface to generate MWE annotations for the first time in a dataset of MWE identification.
Outcome: The proposed model outperforms existing models on the DiMSUM dataset.

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