A machine translation reading list maintained by Tsinghua Natural Language Processing Group
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README.md

Machine Translation Reading List

This is a machine translation reading list maintained by the Tsinghua Natural Language Processing Group.

The past three decades have witnessed the rapid development of machine translation, especially for data-driven approaches such as statistical machine translation (SMT) and neural machine translation (NMT). Due to the dominance of NMT at the present time, priority is given to collecting important, up-to-date NMT papers. The list is still incomplete and the categorization might be inappropriate. Each paper is given its Google Scholar citation count, which will be updated monthly.

We will keep adding papers and improving the list. Any suggestions are welcome!

10 Must Reads

Statistical Machine Translation

Tutorials

Word-based Models

Phrase-based Models

Syntax-based Models

Discriminative Training

System Combination

Human-centered SMT

Interactive SMT

Adaptation

Evaluation

Neural Machine Translation

Tutorials

Model Architecture

Attention Mechanism

Open Vocabulary

Training Objective

Decoding

Low-resource Language Translation

Semi-supervised Learning

Unsupervised Learning

Pivot-based Methods

Data Augmentation Methods

Transfer Learning

Meta Learning

Multi-task Learning

Prior Knowledge Integration

Word/Phrase Constraints

Syntactic/Semantic Constraints

Coverage Constraints

Document-level Translation

Robustness

Interpretability

Linguistic Interpretation

Fairness and Diversity

Efficiency

Pre-Training

Speech Translation

Multi-modality

Ensemble and Reranking

Domain Adaptation

Quality Estimation

Human-centered NMT

Interactive NMT

Automatic Post-Editing

Word Translation and Bilingual Lexicon Induction

Poetry Translation