68 citations · 93 across the 7 of their papers we have counts for
7 papers
OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models
Nikolay Bogoychev, Jelmer van der Linde, Graeme Nail +7
Developing high quality machine translation systems is a labour intensive, challenging and confusing process for newcomers to the field. We present a pair of tools OpusCleaner and…
Assessing the Reliability of Large Language Model Knowledge
Weixuan Wang, Barry Haddow, Alexandra Birch +1
Large language models (LLMs) have been treated as knowledge bases due to their strong performance in knowledge probing tasks. LLMs are typically evaluated using accuracy, yet this…
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…
Efficient CTC Regularization via Coarse Labels for End-to-End Speech Translation
Biao Zhang, Barry Haddow, Rico Sennrich
For end-to-end speech translation, regularizing the encoder with the Connectionist Temporal Classification (CTC) objective using the source transcript or target translation as labe…
Prompting Large Language Model for Machine Translation: A Case Study
Biao Zhang, Barry Haddow, Alexandra Birch
Research on prompting has shown excellent performance with little or even no supervised training across many tasks. However, prompting for machine translation is still under-explor…
Quantifying Synthesis and Fusion and their Impact on Machine Translation
Arturo Oncevay, Duygu Ataman, Niels van Berkel +3
Theoretical work in morphological typology offers the possibility of measuring morphological diversity on a continuous scale. However, literature in Natural Language Processing (NL…