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Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder
Fahim Dalvi
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Nadir Durrani
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Hassan Sajjad
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Yonatan Belinkov
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Stephan Vogel
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Paper Details:
Month: November
Year: 2017
Location: Taipei, Taiwan
Venue:
IJCNLP |
Citations
URL
Challenges of language technologies for the indigenous languages of the Americas
Manuel Mager
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Ximena Gutierrez-Vasques
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Gerardo Sierra
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Ivan Meza-Ruiz
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Tailoring Neural Architectures for Translating from Morphologically Rich Languages
Peyman Passban
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Andy Way
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Qun Liu
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Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation
Adam Poliak
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Aparajita Haldar
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Rachel Rudinger
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J. Edward Hu
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Ellie Pavlick
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Aaron Steven White
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Benjamin Van Durme
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The Lazy Encoder: A Fine-Grained Analysis of the Role of Morphology in Neural Machine Translation
Arianna Bisazza
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Clara Tump
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Neural Machine Translation for Bilingually Scarce Scenarios: a Deep Multi-Task Learning Approach
Poorya Zaremoodi
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Gholamreza Haffari
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On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference
Adam Poliak
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Yonatan Belinkov
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James Glass
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Benjamin Van Durme
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What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties
Alexis Conneau
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German Kruszewski
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Guillaume Lample
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Loïc Barrault
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Marco Baroni
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Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation
Poorya Zaremoodi
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Wray Buntine
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Gholamreza Haffari
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Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov
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James Glass
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Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings
Pamela Shapiro
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Kevin Duh
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Portable, layer-wise task performance monitoring for NLP models
Tom Lippincott
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https://github.com/
Field Of Study
Linguistic Trends
Embeddings
Syntax
Morphology
Task
Tagging
Machine Translation
Language
Multilingual
English
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