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Intelligent Translation Memory Matching and Retrieval with Sentence Encoders

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arxiv 2004.12894 v1 pith:URDXJJN6 submitted 2020-04-27 cs.CL

Tharindu Ranasinghe , Constantin Orasan , Ruslan Mitkov This is my paper · ORCID
classification cs.CL
keywords translationmatchingmemoriesretrievingsystemsalgorithmsdistanceedit
verification ladder T0 review T1 audit T2 compute T3 formal

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Matching and retrieving previously translated segments from a Translation Memory is the key functionality in Translation Memories systems. However this matching and retrieving process is still limited to algorithms based on edit distance which we have identified as a major drawback in Translation Memories systems. In this paper we introduce sentence encoders to improve the matching and retrieving process in Translation Memories systems - an effective and efficient solution to replace edit distance based algorithms.

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  1. Looking under the Wrong Lamppost: On the Limitations of Automated Translation Quality Estimation

    cs.CL 2026-08 conditional novelty 5.0 of 10

    Segment-level QE scores are not reliable enough to gate translation review, according to a new 104k-segment evaluation and a synthesis of prior critiques.

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