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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 51–75 of 1773 papers

TitleStatusHype
Can the Variation of Model Weights be used as a Criterion for Self-Paced Multilingual NMT?—0
TIMeSynC: Temporal Intent Modelling with Synchronized Context Encodings for Financial Service Applications—0
Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation—0
Contrastive Token Learning with Similarity Decay for Repetition Suppression in Machine Translation—0
Cross-lingual Human-Preference Alignment for Neural Machine Translation with Direct Quality Optimization—0
Exploring the traditional NMT model and Large Language Model for chat translation—0
Multilingual Transfer and Domain Adaptation for Low-Resource Languages of Spain—0
HW-TSC's Submission to the CCMT 2024 Machine Translation Tasks—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
EMMeTT: Efficient Multimodal Machine Translation Training—0
Thesis proposal: Are We Losing Textual Diversity to Natural Language Processing?—0
Vision-fused Attack: Advancing Aggressive and Stealthy Adversarial Text against Neural Machine TranslationCode0
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
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
Towards Inducing Document-Level Abilities in Standard Multilingual Neural Machine Translation Models—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
Language-Informed Beam Search Decoding for Multilingual Machine TranslationCode1
Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMsCode0
Enhancing AI-based Generation of Software Exploits with Contextual Information—0
Nested Music Transformer: Sequentially Decoding Compound Tokens in Symbolic Music and Audio GenerationCode1
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translationCode0
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