105 citations · 125 across the 50 of their papers we have counts for
7 papers · 2 filters
Linguistically inspired morphological inflection with a sequence to sequence model
Eleni Metheniti, Guenter Neumann, Josef van Genabith
Inflection is an essential part of every human language's morphology, yet little effort has been made to unify linguistic theory and computational methods in recent years. Methods…
Learning Hard Retrieval Decoder Attention for Transformers
Hongfei Xu, Qiuhui Liu, Josef van Genabith +1
The Transformer translation model is based on the multi-head attention mechanism, which can be parallelized easily. The multi-head attention network performs the scaled dot-product…
Learning Source Phrase Representations for Neural Machine Translation
Hongfei Xu, Josef van Genabith, Deyi Xiong +2
The Transformer translation model (Vaswani et al., 2017) based on a multi-head attention mechanism can be computed effectively in parallel and has significantly pushed forward the…
Dynamically Adjusting Transformer Batch Size by Monitoring Gradient Direction Change
Hongfei Xu, Josef van Genabith, Deyi Xiong +1
The choice of hyper-parameters affects the performance of neural models. While much previous research (Sutskever et al., 2013; Duchi et al., 2011; Kingma and Ba, 2015) focuses on a…
Self-Induced Curriculum Learning in Self-Supervised Neural Machine Translation
Dana Ruiter, Josef van Genabith, Cristina España-Bonet
Self-supervised neural machine translation (SSNMT) jointly learns to identify and select suitable training data from comparable (rather than parallel) corpora and to translate, in…
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
Georg Rehm, Katrin Marheinecke, Stefanie Hegele +44
Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cr…