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Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer ...
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How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation? ...
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Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank ...
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Incorporating Terminology Constraints in Automatic Post-Editing ...
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EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints ...
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Controlling Neural Machine Translation Formality with Synthetic Supervision ...
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Controlling Text Complexity in Neural Machine Translation ...
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Identifying Semantic Divergences in Parallel Text without Annotations ...
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Bi-Directional Neural Machine Translation with Synthetic Parallel Data ...
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Multi-Task Neural Models for Translating Between Styles Within and Across Languages ...
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Abstract:
Generating natural language requires conveying content in an appropriate style. We explore two related tasks on generating text of varying formality: monolingual formality transfer and formality-sensitive machine translation. We propose to solve these tasks jointly using multi-task learning, and show that our models achieve state-of-the-art performance for formality transfer and are able to perform formality-sensitive translation without being explicitly trained on style-annotated translation examples. ... : Accepted at the 27th International Conference on Computational Linguistics (COLING 2018) ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1806.04357 https://dx.doi.org/10.48550/arxiv.1806.04357
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Robust Cross-lingual Hypernymy Detection using Dependency Context ...
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