SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 751–800 of 1773 papers

TitleStatusHype
Crafting Adversarial Examples for Neural Machine Translation—0
Automatically Generating Commit Messages from Diffs using Neural Machine Translation—0
Improving NMT via Filtered Back Translation—0
Improving Robustness in Real-World Neural Machine Translation Engines—0
Coverage Embedding Models for Neural Machine Translation—0
Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestions—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
Improving Autoregressive NLP Tasks via Modular Linearized Attention—0
Improving the Robustness of Speech Translation—0
Improving Zero-shot Multilingual Neural Machine Translation for Low-Resource Languages—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Improving Zero-shot Neural Machine Translation on Language-specific Encoders-Decoders—0
Automated Text Simplification as a Preprocessing Step for Machine Translation into an Under-resourced Language—0
An approach for mistranslation removal from popular dataset for Indic MT Task—0
Improvement in Machine Translation with Generative Adversarial Networks—0
Incorporating External Annotation to improve Named Entity Translation in NMT—0
Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations—0
Incorporating Global Visual Features into Attention-based Neural Machine Translation.—0
Incorporating Source-Side Phrase Structures into Neural Machine Translation—0
Incorporating Source Syntax into Transformer-Based Neural Machine Translation—0
Incorporating Syntactic Uncertainty in Neural Machine Translation with a Forest-to-Sequence Model—0
Incorporating translation quality estimation into Chinese-Korean neural machine translation—0
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring—0
Incorporating Word Reordering Knowledge into Attention-based Neural Machine Translation—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Improved Neural Machine Translation using Side Information—0
Correcting Length Bias in Neural Machine Translation—0
Improved English to Russian Translation by Neural Suffix Prediction—0
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits—0
Inducing Grammars with and for Neural Machine Translation—0
Inference-only sub-character decomposition improves translation of unseen logographic characters—0
Information-Propogation-Enhanced Neural Machine Translation by Relation Model—0
Improved English to Hindi Multimodal Neural Machine Translation—0
Insights from Gathering MT Productivity Metrics at Scale—0
Corpus Augmentation by Sentence Segmentation for Low-Resource Neural Machine Translation—0
Integrating Multi-Head Convolutional Encoders with Cross-Attention for Improved SPARQL Query Translation—0
Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model—0
Implications of Multi-Word Expressions on English to Bharti Braille Machine Translation—0
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages—0
Integrating Vectorized Lexical Constraints for Neural Machine Translation—0
Corpora for Document-Level Neural Machine Translation—0
AutoLoss: Learning Discrete Schedule for Alternate Optimization—0
An Analysis on Automated Metrics for Evaluating Japanese-English Chat Translation—0
Interactive Visualization and Manipulation of Attention-based Neural Machine Translation—0
Illinois Japanese English News Translation for WMT 2021—0
Introducing EM-FT for Manipuri-English Neural Machine Translation—0
Introducing the CURLICAT Corpora: Seven-language Domain Specific Annotated Corpora from Curated Sources—0
Introducing the NewsPaLM MBR and QE Dataset: LLM-Generated High-Quality Parallel Data Outperforms Traditional Web-Crawled Data—0
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments—0
IITP-MT System for Gujarati-English News Translation Task at WMT 2019—0
Show:102550
← PrevPage 16 of 36Next →

No leaderboard results yet.