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WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context

arXiv 2004.15016 ↗First posted 30 Apr 2020cs.CLcited by 13

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Abstract (arXiv)

We present WiC-TSV, a new multi-domain evaluation benchmark for Word Sense Disambiguation. More specifically, we introduce a framework for Target Sense Verification of Words in Context which grounds its uniqueness in the formulation as a binary classification task thus being independent of external sense inventories, and the coverage of various domains. This makes the dataset highly flexible for the evaluation of a diverse set of models and systems in and across domains. WiC-TSV provides three different evaluation settings, depending on the input signals provided to the model. We set baseline performance on the dataset using state-of-the-art language models. Experimental results show that even though these models can perform decently on the task, there remains a gap between machine and human performance, especially in out-of-domain settings. WiC-TSV data is available at https://competitions.codalab.org/competitions/23683

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Apr 2020.

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Citing papers per year: 2021: 4; 2022: 1; 2023: 4; 2024: 1; 2025: 1; 2026: 2.

13 papers.

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