2 citations · 2 across the 8 of their papers we have counts for
10 papers
Pitfalls and Outlooks in Using COMET
Vilém Zouhar, Pinzhen Chen, Tsz Kin Lam +2
The COMET metric has blazed a trail in the machine translation community, given its strong correlation with human judgements of translation quality. Its success stems from being a…
Sentence Ambiguity, Grammaticality and Complexity Probes
Sunit Bhattacharya, Vilém Zouhar, Ondřej Bojar
It is unclear whether, how and where large pre-trained language models capture subtle linguistic traits like ambiguity, grammaticality and sentence complexity. We present results o…
Knowledge Base Index Compression via Dimensionality and Precision Reduction
Vilém Zouhar, Marius Mosbach, Miaoran Zhang +1
Recently neural network based approaches to knowledge-intensive NLP tasks, such as question answering, started to rely heavily on the combination of neural retrievers and readers.…
EMMT: A simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenarios
Sunit Bhattacharya, Věra Kloudová, Vilém Zouhar +1
We present the Eyetracked Multi-Modal Translation (EMMT) corpus, a dataset containing monocular eye movement recordings, audio and 4-electrode electroencephalogram (EEG) data of 43…
Artefact Retrieval: Overview of NLP Models with Knowledge Base Access
Vilém Zouhar, Marius Mosbach, Debanjali Biswas +1
Many NLP models gain performance by having access to a knowledge base. A lot of research has been devoted to devising and improving the way the knowledge base is accessed and incor…
Neural Machine Translation Quality and Post-Editing Performance
Vilém Zouhar, Aleš Tamchyna, Martin Popel +1
We test the natural expectation that using MT in professional translation saves human processing time. The last such study was carried out by Sanchez-Torron and Koehn (2016) with p…