mlsanityData to 7 Oct 2026

Neural Machine Translation and Sequence-to-sequence Models: A Tutorial

arXiv 1703.01619 ↗First posted 5 Mar 2017cs.CL cs.LG stat.MLcited by 25

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Abstract (arXiv)

This tutorial introduces a new and powerful set of techniques variously called "neural machine translation" or "neural sequence-to-sequence models". These techniques have been used in a number of tasks regarding the handling of human language, and can be a powerful tool in the toolbox of anyone who wants to model sequential data of some sort. The tutorial assumes that the reader knows the basics of math and programming, but does not assume any particular experience with neural networks or natural language processing. It attempts to explain the intuition behind the various methods covered, then delves into them with enough mathematical detail to understand them concretely, and culiminates with a suggestion for an implementation exercise, where readers can test that they understood the content in practice.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Mar 2017.

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Citing papers per year: 2021: 9; 2022: 7; 2023: 3; 2024: 4; 2025: 2.

25 papers.

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  1. 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Surveycited by 46
  2. 2021An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problemcited by 22
  3. 2022PromptEHR: Conditional Electronic Healthcare Records Generation with Prompt Learningcited by 22
  4. 2022Transferable and Adaptable Driving Behavior Predictioncited by 20
  5. 2021Generating Relevant and Coherent Dialogue Responses using Self-separated Conditional Variational AutoEncoderscited by 18
  6. 2022Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Surveycited by 9
  7. 2023Neural Machine Translation for the Indigenous Languages of the Americas: An Introductioncited by 7
  8. 2021Online Adaptation of Neural Network Models by Modified Extended Kalman Filter for Customizable and Transferable Driving Behavior Predictioncited by 6
  9. 2021Attention Forcing for Machine Translationcited by 3
  10. 2022Word Alignment in the Era of Deep Learning: A Tutorialcited by 3
  11. 2023Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning Acceleratorcited by 3
  12. 2024Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptationscited by 3
13 more
  1. 2024Muscles in Time: Learning to Understand Human Motion by Simulating Muscle Activationscited by 3
  2. 2021Transformer-based Map Matching Model with Limited Ground-Truth Data using Transfer-Learning Approachcited by 2
  3. 2022PharmMT: A Neural Machine Translation Approach to Simplify Prescription Directionscited by 2
  4. 2024AgriLLM: Harnessing Transformers for Farmer Queriescited by 2
  5. 2024Large Language Model Evaluation via Matrix Nuclear-Normcited by 2
  6. 2021Unsupervised Transfer Learning in Multilingual Neural Machine Translation with Cross-Lingual Word Embeddingscited by 1
  7. 2021Vision-Guided Forecasting -- Visual Context for Multi-Horizon Time Series Forecastingcited by 1
  8. 2022Modeling Complex Dialogue Mappings via Sentence Semantic Segmentation Guided Conditional Variational Auto-Encodercited by 1
  9. 2023Optimizing Large Language Models to Expedite the Development of Smart Contractscited by 1
  10. 2025Intent-Aware Neural Query Reformulation for Behavior-Aligned Product Searchcited by 1
  11. 2021English-to-Chinese Transliteration with Phonetic Back-transliterationcited by 0
  12. 2022Deliberation Networks and How to Train Themcited by 0
  13. 2025Low-Resource Neural Machine Translation Using Recurrent Neural Networks and Transfer Learning: A Case Study on English-to-Igbocited by 0