12 papers
Translation Heads: Disentangling meaning from language in LLM-based machine translation
Théo Lasnier, Armel Zebaze, Djamé Seddah +2
Mechanistic Interpretability (MI) seeks to explain how neural networks implement their capabilities, but the scale of Large Language Models (LLMs) has limited prior MI work in Mach…
When the Gold Standard Isn't Necessarily Standard: Challenges of Evaluating the Translation of User-Generated Content
Lydia Nishimwe, Benoît Sagot, Rachel Bawden
User-generated content (UGC) is characterised by frequent use of non-standard language, from spelling errors to expressive choices such as slang, character repetitions, and emojis.…
Gaperon: A Peppered English-French Generative Language Model Suite
Nathan Godey, Wissam Antoun, Rian Touchent +4
We release Gaperon, a fully open suite of French-English-coding language models designed to advance transparency and reproducibility in large-scale model training. The Gaperon fami…
LLM Reasoning for Machine Translation: Synthetic Data Generation over Thinking Tokens
Armel Zebaze, Rachel Bawden, Benoît Sagot
Large reasoning models (LRMs) have led to new possibilities in terms of problem-solving, through the devising of a natural language thought process prior to answering a query. Whil…
AFRIDOC-MT: Document-level MT Corpus for African Languages
Jesujoba O. Alabi, Israel Abebe Azime, Miaoran Zhang +13
This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yorùbá, and Zulu. The…
Explicit Learning and the LLM in Machine Translation
Malik Marmonier, Rachel Bawden, Benoît Sagot
This study explores an LLM's ability to learn new languages using explanations found in a grammar book, a process we term "explicit learning." To rigorously assess this ability, we…