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1
On Homophony and Rényi Entropy ...
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2
Backtranslation in Neural Morphological Inflection ...
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3
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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4
Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
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5
An Information-Theoretic Characterization of Morphological Fusion ...
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6
Analyzing the Surprising Variability in Word Embedding Stability Across Languages ...
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7
Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings ...
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8
STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
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9
Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ...
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10
Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation ...
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11
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach ...
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12
Sequence Length is a Domain: Length-based Overfitting in Transformer Models ...
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13
Speechformer: Reducing Information Loss in Direct Speech Translation ...
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14
Data and Parameter Scaling Laws for Neural Machine Translation ...
Abstract: We observe that the development cross-entropy loss of supervised neural machine translation models scales like a power law with the amount of training data and the number of non-embedding parameters in the model. We discuss some practical implications of these results, such as predicting BLEU achieved by large scale models and predicting the ROI of labeling data in low-resource language pairs. ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
URL: https://dx.doi.org/10.48448/qadb-fq86
https://underline.io/lecture/38103-data-and-parameter-scaling-laws-for-neural-machine-translation
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15
A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders ...
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16
Universal Simultaneous Machine Translation with Mixture-of-Experts Wait-k Policy ...
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17
Learning to Rewrite for Non-Autoregressive Neural Machine Translation ...
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18
Towards Making the Most of Dialogue Characteristics for Neural Chat Translation ...
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19
Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation ...
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20
Sometimes We Want Ungrammatical Translations ...
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