mlsanityData to 14 Oct 2026

Optimizing example selection for retrieval-augmented machine translation with translation memories

arXiv 2405.15070 ↗First posted 23 May 2024cs.CLcited by 0

On the map: Retrieval-augmented generation → Generation and context integration

Abstract (arXiv)

Retrieval-augmented machine translation leverages examples from a translation memory by retrieving similar instances. These examples are used to condition the predictions of a neural decoder. We aim to improve the upstream retrieval step and consider a fixed downstream edit-based model: the multi-Levenshtein Transformer. The task consists of finding a set of examples that maximizes the overall coverage of the source sentence. To this end, we rely on the theory of submodular functions and explore new algorithms to optimize this coverage. We evaluate the resulting performance gains for the machine translation task.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Generation and context integration, one of 15 directions in Retrieval-augmented generation. Builds on 3 of its 5 references that are in the map. First posted on arXiv 23 May 2024.

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3 of 5 references.

References · 3

  1. 2022A Survey on Retrieval-Augmented Text Generationcited by 158
  2. 2023In-context Learning as Maintaining Coherency: A Study of On-the-fly Machine Translation Using Large Language Modelscited by 10
  3. 2022Nearest Neighbor Non-autoregressive Text Generationcited by 7

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  1. 2024Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison
  2. 2023Towards Example-Based NMT with Multi-Levenshtein Transformers
  3. 2022Neural Machine Translation with Contrastive Translation Memories
  4. 2025Improving Retrieval-Augmented Neural Machine Translation with Monolingual Data
  5. 2022Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestions
  6. 2022Improving Retrieval Augmented Neural Machine Translation by Controlling Source and Fuzzy-Match Interactions
  7. 2026RASST: Retrieval-Augmented Simultaneous Speech Translation
  8. 2024Retrieval-Augmented Machine Translation with Unstructured Knowledge