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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 226–250 of 1773 papers

TitleStatusHype
N-gram Prediction and Word Difference Representations for Language Modeling—0
Integrating Multi-Head Convolutional Encoders with Cross-Attention for Improved SPARQL Query Translation—0
Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation—0
High-Quality Data Augmentation for Low-Resource NMT: Combining a Translation Memory, a GAN Generator, and Filtering—0
Towards Inducing Document-Level Abilities in Standard Multilingual Neural Machine Translation Models—0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
PyMarian: Fast Neural Machine Translation and Evaluation in Python—0
Introducing the NewsPaLM MBR and QE Dataset: LLM-Generated High-Quality Parallel Data Outperforms Traditional Web-Crawled Data—0
Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMsCode0
Enhancing AI-based Generation of Software Exploits with Contextual Information—0
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translationCode0
The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs—0
Translate-and-Revise: Boosting Large Language Models for Constrained Translation—0
Segment-Based Interactive Machine Translation for Pre-trained Models—0
Enhancing Low-Resource NMT with a Multilingual Encoder and Knowledge Distillation: A Case StudyCode0
Rethinking Targeted Adversarial Attacks For Neural Machine TranslationCode0
Enhancing Language Learning through Technology: Introducing a New English-Azerbaijani (Arabic Script) Parallel Corpus—0
Language Portability Strategies for Open-domain Dialogue with Pre-trained Language Models from High to Low Resource Languages—0
Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation—0
M3T: A New Benchmark Dataset for Multi-Modal Document-Level Machine TranslationCode0
Efficient k-Nearest-Neighbor Machine Translation with Dynamic RetrievalCode0
Understanding and Addressing the Under-Translation Problem from the Perspective of Decoding Objective—0
Integrating Multi-scale Contextualized Information for Byte-based Neural Machine TranslationCode0
Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study—0
Reinforcement Learning for Edit-Based Non-Autoregressive Neural Machine Translation—0
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