Papers by Patrick Simianer
Measuring Immediate Adaptation Performance for Neural Machine Translation (N19-1)
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| Challenge: | Incremental domain adaptation improves interactive machine translation performance . users of interactive systems are sensitive to the speed of adaptation . |
| Approach: | They propose to measure the speed of lexical acquisition for in-domain vocabulary . they propose to use this to choose the most suitable adaptation method for neural machine translation . |
| Outcome: | The proposed measures measure the speed of lexical acquisition for in-domain vocabulary . they show that the most suitable adaptation method is chosen from a range of different techniques . |
Compact Personalized Models for Neural Machine Translation (D18-1)
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| Challenge: | a large proportion of model parameters can be frozen during adaptation with minimal or no reduction in translation quality. |
| Approach: | They propose gradient-based domain adaptation methods for self-attentive machine translation models . they encourage structured sparsity in the set of offset tensors during learning . |
| Outcome: | The proposed method achieves high space and time efficiency using sparse models . the results compare the proposed method with incremental adaptation . |