2 citations · 2 across the 24 of their papers we have counts for
3 papers · 1 filter
Turning English-centric LLMs Into Polyglots: How Much Multilinguality Is Needed?
Tannon Kew, Florian Schottmann, Rico Sennrich
The vast majority of today's large language models (LLMs) are English-centric, having been pretrained predominantly on English text. Yet, in order to meet user expectations, models…
Trained MT Metrics Learn to Cope with Machine-translated References
Jannis Vamvas, Tobias Domhan, Sony Trenous +2
Neural metrics trained on human evaluations of MT tend to correlate well with human judgments, but their behavior is not fully understood. In this paper, we perform a controlled ex…
Investigating Multi-Pivot Ensembling with Massively Multilingual Machine Translation Models
Alireza Mohammadshahi, Jannis Vamvas, Rico Sennrich
Massively multilingual machine translation models allow for the translation of a large number of languages with a single model, but have limited performance on low- and very-low-re…