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Team ÚFAL at CMCL 2022 Shared Task: Figuring out the correct recipe for predicting Eye-Tracking features using Pretrained Language Models ...
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Abstract:
Eye-Tracking data is a very useful source of information to study cognition and especially language comprehension in humans. In this paper, we describe our systems for the CMCL 2022 shared task on predicting eye-tracking information. We describe our experiments with pretrained models like BERT and XLM and the different ways in which we used those representations to predict four eye-tracking features. Along with analysing the effect of using two different kinds of pretrained multilingual language models and different ways of pooling the tokenlevel representations, we also explore how contextual information affects the performance of the systems. Finally, we also explore if factors like augmenting linguistic information affect the predictions. Our submissions achieved an average MAE of 5.72 and ranked 5th in the shared task. The average MAE showed further reduction to 5.25 in post task evaluation. ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.2204.04998
https://arxiv.org/abs/2204.04998
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Pushing the right buttons: adversarial evaluation of quality estimation
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In: Proceedings of the Sixth Conference on Machine Translation ; 625 ; 638 (2022)
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THEaiTRobot 1.0
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Rosa, Rudolf; Dušek, Ondřej; Kocmi, Tom. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2021. : The Švanda Theatre in Smíchov, 2021. : The Academy of Performing Arts in Prague, Theatre Faculty (DAMU), 2021
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Ptakopět data: the dataset for experiments on outbound translation
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Unsupervised Multilingual Sentence Embeddings for Parallel Corpus Mining ...
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CUNI systems for WMT21: Multilingual Low-Resource Translation for Indo-European Languages Shared Task ...
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Lost in Interpreting: Speech Translation from Source or Interpreter? ...
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Sequence Length is a Domain: Length-based Overfitting in Transformer Models ...
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Neural Machine Translation Quality and Post-Editing Performance ...
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End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages ...
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