# Intelligent Translation Memory Matching and Retrieval with Sentence Encoders

arXiv: https://arxiv.org/abs/2004.12894 · HTML: https://mlsanity.com/paper/2004.12894/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2020.

## Built on by (most cited first, 3 of 3)

- [UniTE: Unified Translation Evaluation](https://mlsanity.com/paper/2204.13346/) (2022)
- [Looking under the Wrong Lamppost: On the Limitations of Automated Translation Quality Estimation](https://mlsanity.com/paper/2608.03577/) (2026)
- [Cross-lingual neural fuzzy matching for exploiting target-language monolingual corpora in computer-aided translation](https://mlsanity.com/paper/2401.08374/) (2024)

## Abstract (arXiv)

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.