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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 1451–1500 of 1773 papers

TitleStatusHype
Character-Aware Decoder for Translation into Morphologically Rich Languages—0
Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation—0
Character-based NMT with Transformer—0
Character-level NMT and language similarity—0
Character-level Transformer-based Neural Machine Translation—0
Checkpoint Reranking: An Approach to Select Better Hypothesis for Neural Machine Translation Systems—0
Checks and Strategies for Enabling Code-Switched Machine Translation—0
Chinese-Portuguese Machine Translation: A Study on Building Parallel Corpora from Comparable Texts—0
Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Task—0
Chunk-based Decoder for Neural Machine Translation—0
CKY-based Convolutional Attention for Neural Machine Translation—0
Clause Attention based on Signal Words Division—0
CMU’s Machine Translation System for IWSLT 2019—0
C-NMT: A Collaborative Inference Framework for Neural Machine Translation—0
Code-switching pre-training for neural machine translation—0
Code-Switching with Word Senses for Pretraining in Neural Machine Translation—0
CODET: A Benchmark for Contrastive Dialectal Evaluation of Machine Translation—0
Code Translation with Compiler Representations—0
Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation—0
Combination of Neural Machine Translation Systems at WMT20—0
Combining PBSMT and NMT Back-translated Data for Efficient NMT—0
Combining Sequence Distillation and Transfer Learning for Efficient Low-Resource Neural Machine Translation Models—0
Combining SMT and NMT Back-Translated Data for Efficient NMT—0
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation—0
Combining Translation Memory with Neural Machine Translation—0
Combining Word and Character Vector Representation on Neural Machine Translation—0
Communication-Efficient Federated Learning for Neural Machine Translation—0
Comparative Evaluation of NMT with Established SMT Programs—0
Comparing a Hand-crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation—0
Comparing and combining tagging with different decoding algorithms for back-translation in NMT: learnings from a low resource scenario—0
Comparing MT Approaches for Text Normalization—0
Comparing Multilingual NMT Models and Pivoting—0
Comparison between NMT and PBSMT Performance for Translating Noisy User-Generated Content—0
Comparison of SMT and NMT trained with large Patent Corpora: Japio at WAT2017—0
Comparison of the effects of attention mechanism on translation tasks of different lengths of ambiguous words—0
Complex Question Answering on knowledge graphs using machine translation and multi-task learning—0
Compositional Representation of Morphologically-Rich Input for Neural Machine Translation—0
Compressing Neural Machine Translation Models with 4-bit Precision—0
Concept Equalization to Guide Correct Training of Neural Machine Translation—0
Conditional Variational Autoencoder for Neural Machine Translation—0
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT—0
Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation—0
Conflict as an Inverse of Attention in Sequence Relationship—0
Constraining the Transformer NMT Model with Heuristic Grid Beam Search—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language—0
Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20—0
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT—0
Content Word Aware Neural Machine Translation—0
Context-Adaptive Document-Level Neural Machine Translation—0
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