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Predicting Word Similarity in Context with Referential Translation Machines

arXiv 2407.06230 ↗First posted 7 Jul 2024cs.CL cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 3 of its 25 references that are in the map. First posted on arXiv 7 Jul 2024.

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References · 3

  1. 2014SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimationcited by 170
  2. 2016SimVerb-3500: A Large-Scale Evaluation Set of Verb Similaritycited by 44
  3. 2018Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Modelscited by 11

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