68 citations · 234 across the 28 of their papers we have counts for
36 papers
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
EuroGEST: Investigating gender stereotypes in multilingual language models
Jacqueline Rowe, Mateusz Klimaszewski, Liane Guillou +2
Large language models increasingly support multiple languages, yet most benchmarks for gender bias remain English-centric. We introduce EuroGEST, a dataset designed to measure gend…
Towards Effective Disambiguation for Machine Translation with Large Language Models
Vivek Iyer, Pinzhen Chen, Alexandra Birch
Resolving semantic ambiguity has long been recognised as a central challenge in the field of Machine Translation. Recent work on benchmarking translation performance on ambiguous s…
An Open Dataset and Model for Language Identification
Laurie Burchell, Alexandra Birch, Nikolay Bogoychev +1
Language identification (LID) is a fundamental step in many natural language processing pipelines. However, current LID systems are far from perfect, particularly on lower-resource…
When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale
Christos Baziotis, Biao Zhang, Alexandra Birch +1
Multilingual machine translation (MMT), trained on a mixture of parallel and monolingual data, is key for improving translation in low-resource language pairs. However, the literat…
Hallucinations in Large Multilingual Translation Models
Nuno M. Guerreiro, Duarte Alves, Jonas Waldendorf +4
Large-scale multilingual machine translation systems have demonstrated remarkable ability to translate directly between numerous languages, making them increasingly appealing for r…