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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 651–700 of 1773 papers

TitleStatusHype
HintedBT: Augmenting Back-Translation with Quality and Transliteration Hints—0
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
Fixing exposure bias with imitation learning needs powerful oracles—0
A Large-Scale Study of Machine Translation in the Turkic Languages—0
Vision Matters When It Should: Sanity Checking Multimodal Machine Translation ModelsCode0
Attention based Sequence to Sequence Learning for Machine Translation of Low Resourced Indic Languages -- A case of Sanskrit to Hindi—0
Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT—0
Low Resource Multimodal Neural Machine Translation of English-Hindi in News Domain—0
Multilingual Multi-Domain NMT for Indian Languages—0
Neural Machine Translation for Sinhala-English Code-Mixed Text—0
On Machine Translation of User Reviews—0
Transformer with Syntactic Position Encoding for Machine Translation—0
Mining Bilingual Word Pairs from Comparable Corpus using Apache Spark Framework—0
Secoco: Self-Correcting Encoding for Neural Machine Translation—0
YANMTT: Yet Another Neural Machine Translation Toolkit—0
Attentive fine-tuning of Transformers for Translation of low-resourced languages @LoResMT 2021Code0
The paradox of the compositionality of natural language: a neural machine translation case studyCode0
Icelandic Parallel Abstracts Corpus—0
A Dynamic Head Importance Computation Mechanism for Neural Machine Translation—0
Modeling Task-Aware MIMO Cardinality for Efficient Multilingual Neural Machine Translation—0
Samsung R&D Institute Poland submission to WAT 2021 Indic Language Multilingual Task—0
Investigating Softmax Tempering for Training Neural Machine Translation Models—0
ANVITA Machine Translation System for WAT 2021 MultiIndicMT Shared Task—0
Pre-training Methods for Neural Machine Translation—0
ON-TRAC’ systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks—0
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training—0
Investigating Active Learning in Interactive Neural Machine Translation—0
Multilingual Machine Translation Systems at WAT 2021: One-to-Many and Many-to-One Transformer based NMT—0
An Empirical Study on Adversarial Attack on NMT: Languages and Positions Matter—0
Neural Machine Translation in Low-Resource Setting: a Case Study in English-Marathi Pair—0
NICT-5’s Submission To WAT 2021: MBART Pre-training And In-Domain Fine Tuning For Indic Languages—0
Product Review Translation using Phrase Replacement and Attention Guided Noise Augmentation—0
The USYD-JD Speech Translation System for IWSLT2021—0
Selecting the best data filtering method for NMT training—0
Bering Lab’s Submissions on WAT 2021 Shared Task—0
基于层间知识蒸馏的神经机器翻译(Inter-layer Knowledge Distillation for Neural Machine Translation)—0
On the differences between BERT and MT encoder spaces and how to address them in translation tasks—0
Incorporating translation quality estimation into Chinese-Korean neural machine translation—0
Crafting Adversarial Examples for Neural Machine Translation—0
Morphologically-Guided Segmentation For Translation of Agglutinative Low-Resource LanguagesCode0
TMU NMT System with Japanese BART for the Patent task of WAT 2021—0
A Comparison of Sentence-Weighting Techniques for NMT—0
HI-CMLM: Improve CMLM with Hybrid Decoder Input—0
NHK’s Lexically-Constrained Neural Machine Translation at WAT 2021—0
Point, Disambiguate and Copy: Incorporating Bilingual Dictionaries for Neural Machine Translation—0
IIIT Hyderabad Submission To WAT 2021: Efficient Multilingual NMT systems for Indian languages—0
The University of Edinburgh’s Submission to the IWSLT21 Simultaneous Translation Task—0
A Comparison of Different NMT Approaches to Low-Resource Dutch-Albanian Machine Translation—0
Product Review Translation: Parallel Corpus Creation and Robustness towards User-generated Noisy Text—0
Make the Blind Translator See The World: A Novel Transfer Learning Solution for Multimodal Machine Translation—0
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