Papers by Jakob Verbeek
Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-English (2020.coling-main)
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Maha Elbayad, Michael Ustaszewski, Emmanuelle Esperança-Rodier, Francis Brunet-Manquat, Jakob Verbeek, Laurent Besacier
| Challenge: | Existing studies compare offline and online neural machine translation architectures . we examine the impact of online decoding constraints on the translation quality . |
| Approach: | They evaluate offline and online neural machine translation architectures using human evaluations on English-German and German-English language pairs. |
| Outcome: | The proposed models are particularly sensitive to latency constraints and are well-suited for offline translation tasks. |
Token-level and sequence-level loss smoothing for RNN language models (P18-1)
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| Challenge: | Maximum likelihood estimation treats all sentences that do not match the ground truth as equally poor, ignoring the structure of the output space. |
| Approach: | They propose to extend the reward augmented maximum likelihood approach to token-level loss smoothing by using token-based approaches to improve the model's performance. |
| Outcome: | The proposed model improves on image captioning and machine translation tasks and treats all sentences that do not match the ground truth as poor . |