Predicting Word Similarity in Context with Referential Translation Machines
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914862512209920 |
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| author | Biçici, Ergun |
| author_facet | Biçici, Ergun |
| contents | We identify the similarity between two words in English by casting the task as machine translation performance prediction (MTPP) between the words given the context and the distance between their similarities. We use referential translation machines (RTMs), which allows a common representation for training and test sets and stacked machine learning models. RTMs can achieve the top results in Graded Word Similarity in Context (GWSC) task. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_06230 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Predicting Word Similarity in Context with Referential Translation Machines Biçici, Ergun Computation and Language Artificial Intelligence I.2.7 We identify the similarity between two words in English by casting the task as machine translation performance prediction (MTPP) between the words given the context and the distance between their similarities. We use referential translation machines (RTMs), which allows a common representation for training and test sets and stacked machine learning models. RTMs can achieve the top results in Graded Word Similarity in Context (GWSC) task. |
| title | Predicting Word Similarity in Context with Referential Translation Machines |
| topic | Computation and Language Artificial Intelligence I.2.7 |
| url | https://arxiv.org/abs/2407.06230 |