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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 451–500 of 1773 papers

TitleStatusHype
Domain Adaptation of NMT models for English-Hindi Machine Translation Task : AdapMT Shared Task ICON 2020—0
Domain adapted machine translation: What does catastrophic forgetting forget and why?—0
Domain Control for Neural Machine Translation—0
An In-depth Walkthrough on Evolution of Neural Machine Translation—0
Domain Informed Neural Machine Translation: Developing Translation Services for Healthcare Enterprise—0
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training—0
Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20—0
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?—0
Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models—0
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation—0
Bridging Neural Machine Translation and Bilingual Dictionaries—0
D-PAGE: Diverse Paraphrase Generation—0
Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language—0
A Test Suite for Evaluating Discourse Phenomena in Document-level Neural Machine Translation—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Dual Past and Future for Neural Machine Translation—0
Constraining the Transformer NMT Model with Heuristic Grid Beam Search—0
Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars—0
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation—0
Bridging the Gap between Training and Inference for Neural Machine Translation—0
A Test Suite and Manual Evaluation of Document-Level NMT at WMT19—0
Dynamic Fusion: Attentional Language Model for Neural Machine Translation—0
Building a Parallel Corpus and Training Translation Models Between Luganda and English—0
Dynamic Oracle for Neural Machine Translation in Decoding Phase—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
Dynamic Position Encoding for Transformers—0
Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation—0
A Parallel Corpus of Theses and Dissertations Abstracts—0
A Multi-Task Architecture on Relevance-based Neural Query Translation—0
Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training—0
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT—0
EduMT: Developing Machine Translation System for Educational Content in Indian Languages—0
Improving Neural Machine Translation with Pre-trained Representation—0
Ensemble of Translators with Automatic Selection of the Best Translation -- the submission of FOKUS to the WMT 18 biomedical translation task --—0
Convergences and Divergences between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation—0
Effectively pretraining a speech translation decoder with Machine Translation data—0
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings—0
Effective Use of Target-side Context for Neural Machine Translation—0
Efficient Bilingual Generalization from Neural Transduction Grammar Induction—0
Can Neural Machine Translation be Improved with User Feedback?—0
Efficient Inference for Multilingual Neural Machine Translation—0
Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation—0
Efficient Neural Machine Translation for Low-Resource Languages via Exploiting Related Languages—0
Efficient Neural Machine Translation with Prior Word Alignment—0
Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation—0
Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer—0
Efficient Unsupervised NMT for Related Languages with Cross-Lingual Language Models and Fidelity Objectives—0
Effort-Aware Neural Automatic Post-Editing—0
Efforts Towards Developing a Tamang Nepali Machine Translation System—0
Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission—0
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