65 citations · 96 across the 12 of their papers we have counts for
13 papers
When Does Reasoning Help in Machine Translation? A Hierarchical Analysis of LRM Reasoning Traces
Yuxiang Liu, Jiaming Luo, Eleftheria Briakou +1
Large Reasoning Models increasingly use intermediate traces for machine translation, but it remains unclear when such reasoning helps or hurts. We analyze reasoning traces across m…
Gemma 3 Technical Report
Gemma Team, Aishwarya Kamath, Johan Ferret +209
We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. This version introduces vision underst…
Leveraging Domain Knowledge at Inference Time for LLM Translation: Retrieval versus Generation
Bryan Li, Jiaming Luo, Eleftheria Briakou +1
While large language models (LLMs) have been increasingly adopted for machine translation (MT), their performance for specialist domains such as medicine and law remains an open ch…
SMOL: Professionally translated parallel data for 115 under-represented languages
Isaac Caswell, Elizabeth Nielsen, Jiaming Luo +23
We open-source SMOL (Set of Maximal Overall Leverage), a suite of training data to unlock machine translation for low-resource languages. SMOL has been translated into 124 (and gro…
Overestimation in LLM Evaluation: A Controlled Large-Scale Study on Data Contamination's Impact on Machine Translation
Muhammed Yusuf Kocyigit, Eleftheria Briakou, Daniel Deutsch +3
Data contamination -- the accidental consumption of evaluation examples within the pre-training data -- can undermine the validity of evaluation benchmarks. In this paper, we prese…
How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP
Kushal Tatariya, Artur Kulmizev, Wessel Poelman +6
Wikipedia's perceived high quality and broad language coverage have established it as a fundamental resource in NLP. However, in recent years, such assumptions of high quality have…