5 papers · 1 filter
Reasoning about In-Context Samples for Machine-Translation
Maxime Bouthors, Josep Crego, François Yvon
Large Language Models (LLMs) can be trained to perform chain-of-thoughts reasoning in order to improve the reliability of their responses. In this work, we investigate how explicit…
Improving Retrieval-Augmented Neural Machine Translation with Monolingual Data
Maxime Bouthors, Josep Crego, François Yvon
Conventional retrieval-augmented neural machine translation (RANMT) systems leverage bilingual corpora, e.g., translation memories (TMs). Yet, in many settings, monolingual corpora…
Optimizing example selection for retrieval-augmented machine translation with translation memories
Maxime Bouthors, Josep Crego, François Yvon
Retrieval-augmented machine translation leverages examples from a translation memory by retrieving similar instances. These examples are used to condition the predictions of a neur…
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison
Maxime Bouthors, Josep Crego, Francois Yvon
Retrieval-Augmented Neural Machine Translation (RAMT) architectures retrieve examples from memory to guide the generation process. While most works in this trend explore new ways t…
Towards Example-Based NMT with Multi-Levenshtein Transformers
Maxime Bouthors, Josep Crego, François Yvon
Retrieval-Augmented Machine Translation (RAMT) is attracting growing attention. This is because RAMT not only improves translation metrics, but is also assumed to implement some fo…