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Enabling Robust Grammatical Error Correction in New Domains: Data Sets, Metrics, and Analyses
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 551-566 (2019) (2019)
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22 |
Autosegmental Input Strictly Local Functions
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 157-168 (2019) (2019)
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23 |
Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 403-419 (2019) (2019)
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24 |
Analysis Methods in Neural Language Processing: A Survey
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 49-72 (2019) (2019)
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25 |
Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing
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In: Computational Linguistics, Vol 45, Iss 3, Pp 559-601 (2019) (2019)
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26 |
What Do Language Representations Really Represent?
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In: Computational Linguistics, Vol 45, Iss 2, Pp 381-389 (2019) (2019)
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27 |
CoQA: A Conversational Question Answering Challenge
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 249-266 (2019) (2019)
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28 |
Taking MT Evaluation Metrics to Extremes: Beyond Correlation with Human Judgments
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In: Computational Linguistics, Vol 45, Iss 3, Pp 515-558 (2019) (2019)
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29 |
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 597-610 (2019) (2019)
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Abstract:
We introduce an architecture to learn joint multilingual sentence representations for 93 languages, belonging to more than 30 different families and written in 28 different scripts. Our system uses a single BiLSTM encoder with a shared byte-pair encoding vocabulary for all languages, which is coupled with an auxiliary decoder and trained on publicly available parallel corpora. This enables us to learn a classifier on top of the resulting embeddings using English annotated data only, and transfer it to any of the 93 languages without any modification. Our experiments in cross-lingual natural language inference (XNLI data set), cross-lingual document classification (MLDoc data set), and parallel corpus mining (BUCC data set) show the effectiveness of our approach. We also introduce a new test set of aligned sentences in 112 languages, and show that our sentence embeddings obtain strong results in multilingual similarity search even for low- resource languages. Our implementation, the pre-trained encoder, and the multilingual test set are available at https://github.com/facebookresearch/LASER .
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doi.org/10.1162/tacl_a_00288 https://doaj.org/article/9dbebd9e90f34c40a57b6eb998665289
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30 |
GILE: A Generalized Input-Label Embedding for Text Classification
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 139-155 (2019) (2019)
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31 |
Neural Models of Text Normalization for Speech Applications
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In: Computational Linguistics, Vol 45, Iss 2, Pp 293-337 (2019) (2019)
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32 |
Bayesian Learning of Latent Representations of Language Structures
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In: Computational Linguistics, Vol 45, Iss 2, Pp 199-228 (2019) (2019)
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33 |
Inherent Disagreements in Human Textual Inferences
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 677-694 (2019) (2019)
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34 |
Neural Network Acceptability Judgments
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 625-641 (2019) (2019)
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35 |
Weakly Supervised Domain Detection
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 581-596 (2019) (2019)
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36 |
Contextualized Translations of Phrasal Verbs with Distributional Compositional Semantics and Monolingual Corpora
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In: Computational Linguistics, Vol 45, Iss 3, Pp 395-421 (2019) (2019)
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37 |
Perturbation Based Learning for Structured NLP Tasks with Application to Dependency Parsing
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 643-659 (2019) (2019)
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38 |
Automatic Inference of Sound Correspondence Patterns across Multiple Languages
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In: Computational Linguistics, Vol 45, Iss 1, Pp 137-161 (2019) (2019)
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Parsing Chinese Sentences with Grammatical Relations
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In: Computational Linguistics, Vol 45, Iss 1, Pp 95-136 (2019) (2019)
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SECTOR: A Neural Model for Coherent Topic Segmentation and Classification
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 169-184 (2019) (2019)
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