6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 1 cited
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…
cs.CL2022
CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Task
Jindřich Helcl
We present a non-autoregressive system submission to the WMT 22 Efficient Translation Shared Task. Our system was used by Helcl et al. (2022) in an attempt to provide fair comparis…
cs.CL2020★ 6 cited
Improving Fluency of Non-Autoregressive Machine Translation
Zdeněk Kasner, Jindřich Libovický, Jindřich Helcl
Non-autoregressive (nAR) models for machine translation (MT) manifest superior decoding speed when compared to autoregressive (AR) models, at the expense of impaired fluency of the…