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Neural machine translation with a polysynthetic low resource language [<Journal>]
Ortega, John E. [Verfasser]; Castro Mamani, Richard [Verfasser]; Cho, Kyunghyun [Verfasser]
DNB Subject Category Language
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2
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search ...
BASE
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3
Monotonic Simultaneous Translation with Chunk-wise Reordering and Refinement ...
BASE
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4
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search ...
BASE
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5
The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction ...
BASE
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6
Comparing Test Sets with Item Response Theory ...
BASE
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7
DEEP: DEnoising Entity Pre-training for Neural Machine Translation ...
BASE
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8
VisualSem: A High-quality Knowledge Graph for Vision and Language ...
BASE
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9
Learning to Learn Morphological Inflection for Resource-Poor Languages ...
BASE
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10
Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning ...
BASE
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11
Cold-start universal information extraction
Huang, Lifu. - 2020
BASE
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12
AdapterHub: A Framework for Adapting Transformers
Pfeiffer, Jonas; Ruckle, Andreas; Poth, Clifton. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP 2020), 2020
BASE
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13
Neural Machine Translation with Byte-Level Subwords ...
BASE
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14
Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations ...
Gu, Jiatao; Wang, Yong; Cho, Kyunghyun. - : arXiv, 2019
BASE
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15
Emergent Linguistic Phenomena in Multi-Agent Communication Games ...
BASE
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16
Countering Language Drift via Visual Grounding ...
BASE
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17
Insertion-based Decoding with Automatically Inferred Generation Order
In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 661-676 (2019) (2019)
BASE
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18
Meta-Learning for Low-Resource Neural Machine Translation ...
Gu, Jiatao; Wang, Yong; Chen, Yun. - : arXiv, 2018
BASE
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19
Multi-lingual Common Semantic Space Construction via Cluster-consistent Word Embedding ...
BASE
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20
From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042)
Cho, Kyunghyun; Dyer, Chris; Blunsom, Phil. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2017. : Dagstuhl Reports. Dagstuhl Reports, Volume 7, Issue 1, 2017
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