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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 1651–1700 of 1773 papers

TitleStatusHype
Ensemble Learning for Multi-Source Neural Machine Translation—0
Ensemble of Translators with Automatic Selection of the Best Translation -- the submission of FOKUS to the WMT 18 biomedical translation task --—0
Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translation—0
ESPnet How2 Speech Translation System for IWSLT 2019: Pre-training, Knowledge Distillation, and Going Deeper—0
eTranslation’s Submissions to the WMT 2021 News Translation Task—0
Evaluating and Optimizing the Effectiveness of Neural Machine Translation in Supporting Code Retrieval Models: A Study on the CAT Benchmark—0
Evaluating Discourse Phenomena in Neural Machine Translation—0
Evaluating Explanation Methods for Neural Machine Translation—0
Evaluating Low-Resource Machine Translation between Chinese and Vietnamese with Back-Translation—0
Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages—0
Evaluating Robustness to Input Perturbations for Neural Machine Translation—0
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation—0
Evaluating the Performance of Back-translation for Low Resource English-Marathi Language Pair: CFILT-IITBombay @ LoResMT 2021—0
Evaluating the Supervised and Zero-shot Performance of Multi-lingual Translation Models—0
Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission—0
Evaluation of NMT-Assisted Grammar Transfer for a Multi-Language Configurable Data-to-Text System—0
Evolution Strategy Based Automatic Tuning of Neural Machine Translation Systems—0
Explicit Reordering for Neural Machine Translation—0
Exploiting Deep Representations for Neural Machine Translation—0
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation—0
Exploiting Language Relatedness in Machine Translation Through Domain Adaptation Techniques—0
Exploiting Linguistic Resources for Neural Machine Translation Using Multi-task Learning—0
Exploiting Monolingual Data at Scale for Neural Machine Translation—0
Exploiting Multilingualism in Low-resource Neural Machine Translation via Adversarial Learning—0
Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation—0
Exploiting Neural Query Translation into Cross Lingual Information Retrieval—0
Exploiting Sentential Context for Neural Machine Translation—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
Exploring Hyper-Parameter Optimization for Neural Machine Translation on GPU Architectures—0
Exploring Pair-Wise NMT for Indian Languages—0
Exploring the traditional NMT model and Large Language Model for chat translation—0
Extend Adversarial Policy Against Neural Machine Translation via Unknown Token—0
Extract and Attend: Improving Entity Translation in Neural Machine Translation—0
Extracting In-domain Training Corpora for Neural Machine Translation Using Data Selection Methods—0
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation—0
Factored Neural Machine Translation—0
Factored Neural Machine Translation Architectures—0
Factorized Transformer for Multi-Domain Neural Machine Translation—0
Fast and Accurate Neural Machine Translation with Translation Memory—0
Fast Domain Adaptation for Neural Machine Translation—0
Faster and Lighter Phrase-based Machine Translation Baseline—0
Faster Machine Translation Ensembling with Reinforcement Learning and Competitive Correction—0
Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation—0
Fast-Paced Improvements to Named Entity Handling for Neural Machine Translation—0
Fast Training of NMT Model with Data Sorting—0
FBK’s Neural Machine Translation Systems for IWSLT 2016—0
FeatureBART: Feature Based Sequence-to-Sequence Pre-Training for Low-Resource NMT—0
Feature-rich NMT and SMT post-edited corpora for productivity and evaluation tasks with a subset of MQM-annotated data—0
Federated Nearest Neighbor Machine Translation—0
FFR v1.1: Fon-French Neural Machine Translation—0
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