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Machine Translation

Machine translation is the task of translating a sentence in a source language to a different target language.

Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.

One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.

( Image credit: Google seq2seq )

Papers

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Showing 3001–3050 of 10752 papers

TitleStatusHype
Skeletal Graph Self-Attention: Embedding a Skeleton Inductive Bias into Sign Language Production—0
Protecting Intellectual Property of Language Generation APIs with Lexical WatermarkCode0
Translating Politeness Across Cultures: Case of Hindi and English—0
Multitask Finetuning for Improving Neural Machine Translation in Indian Languages—0
Named Entity-Factored Transformer for Proper Noun Translation—0
Are Ellipses Important for Machine Translation?—0
EduMT: Developing Machine Translation System for Educational Content in Indian Languages—0
Part of Speech Tagging for a Resource Poor Language : Sindhi in Devanagari Script using HMM and CRF—0
lakṣyārtha (Indicated Meaning) of Śabdavyāpāra (Function of a Word) framework from kāvyaśāstra (The Science of Literary Studies) in Samskṛtam : Its application to Literary Machine Translation and other NLP tasks—0
Document Level Hierarchical Transformer—0
An Experiment on Speech-to-Text Translation Systems for Manipuri to English on Low Resource Setting—0
Semantics of Spatio-Directional Geometric Terms of Indian Languages—0
On the Transferability of Massively Multilingual Pretrained Models in the Pretext of the Indo-Aryan and Tibeto-Burman Languages—0
Multi-Task Learning for Improving Gender Accuracy in Neural Machine Translation—0
Prosody Labelled Dataset for Hindi—0
Introduction to ProverbNet: An Online Multilingual Database of Proverbs and Comprehensive Metadata—0
Constrained Decoding for Technical Term Retention in English-Hindi MT—0
KARL-Trans-NER: Knowledge Aware Representation Learning for Named Entity Recognition using Transformers—0
Improvement in Machine Translation with Generative Adversarial Networks—0
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?—0
FastTrees: Parallel Latent Tree-Induction for Faster Sequence EncodingCode0
Generating Usage-related Questions for Preference Elicitation in Conversational Recommender SystemsCode0
Deps-SAN: Neural Machine Translation with Dependency-Scaled Self-Attention Network—0
Efficient Softmax Approximation for Deep Neural Networks with Attention Mechanism—0
Data Processing Matters: SRPH-Konvergen AI's Machine Translation System for WMT'21—0
Detecting Cross-Language Plagiarism using Open Knowledge GraphsCode0
High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics—0
When Does Translation Require Context? A Data-driven, Multilingual Exploration—0
Rare Tokens Degenerate All Tokens: Improving Neural Text Generation via Adaptive Gradient Gating for Rare Token Embeddings—0
INDICXNLI: A Dataset for Studying NLI in Indic Languages—0
NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21—0
Graph Neural Networks for Multiparallel Word Alignment—0
Towards a Fine-Grained Multi-Domain Neural Machine Translation Using Inter-Domain Relationships—0
Focus on the Target’s Vocabulary: Masked Label Smoothing for Machine Translation—0
What Works and Doesn't Work, A Deep Decoder for Neural Machine Translation—0
How to Translate Your Samples and Choose Your Shots? Analyzing Translate-train & Few-shot Cross-lingual Transfer—0
Language-Family Adapters for Multilingual Neural Machine Translation—0
Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding—0
Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip Translation—0
Causal Transformers: Improving the Robustness on Spurious Correlations—0
A Primer in NMTology: What we have understood about NMT—0
Improving Paraphrase Generation models with machine translation generated pre-training—0
Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation—0
A Graph Fusion Approach to Cross-Lingual Machine Reading Comprehension—0
WeTS: A Benchmark for Translation Suggestion—0
Low rank softmax can have unargmaxable classes in theory but rarely in practice—0
Bidirectional Modeling for Simultaneous Neural Machine Translation—0
Quality-Aware Decoding for Neural Machine Translation—0
Integrating Vectorized Lexical Constraints for Neural Machine Translation—0
Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models—0
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All datasetsWMT2014 English-GermanWMT2014 English-FrenchIWSLT2014 German-EnglishACESWMT2016 English-RomanianWMT2016 Romanian-EnglishWMT2014 German-EnglishIWSLT2015 German-EnglishWMT2016 English-GermanIWSLT2015 English-VietnameseIWSLT2015 English-GermanWMT2016 German-English

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Transformer Cycle (Rev)BLEU score35.14—Unverified
2Noisy back-translationBLEU score35—Unverified
3Transformer+Rep(Uni)BLEU score33.89—Unverified
4T5-11BBLEU score32.1—Unverified
5BiBERTBLEU score31.26—Unverified
6Transformer + R-DropBLEU score30.91—Unverified
7Bi-SimCutBLEU score30.78—Unverified
8BERT-fused NMTBLEU score30.75—Unverified
9Data Diversification - TransformerBLEU score30.7—Unverified
10SimCutBLEU score30.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Transformer+BT (ADMIN init)BLEU score46.4—Unverified
2Noisy back-translationBLEU score45.6—Unverified
3mRASP+Fine-TuneBLEU score44.3—Unverified
4Transformer + R-DropBLEU score43.95—Unverified
5Transformer (ADMIN init)BLEU score43.8—Unverified
6AdminBLEU score43.8—Unverified
7BERT-fused NMTBLEU score43.78—Unverified
8MUSE(Paralllel Multi-scale Attention)BLEU score43.5—Unverified
9T5BLEU score43.4—Unverified
10Local Joint Self-attentionBLEU score43.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PiNMTBLEU score40.43—Unverified
2BiBERTBLEU score38.61—Unverified
3Bi-SimCutBLEU score38.37—Unverified
4Cutoff + Relaxed Attention + LMBLEU score37.96—Unverified
5DRDABLEU score37.95—Unverified
6Transformer + R-Drop + CutoffBLEU score37.9—Unverified
7SimCutBLEU score37.81—Unverified
8Cutoff+KneeBLEU score37.78—Unverified
9CutoffBLEU score37.6—Unverified
10CipherDAugBLEU score37.53—Unverified
#ModelMetricClaimedVerifiedStatus
1HWTSC-Teacher-SimScore19.97—Unverified
2MS-COMET-22Score19.89—Unverified
3MS-COMET-QE-22Score19.76—Unverified
4KG-BERTScoreScore17.28—Unverified
5metricx_xl_DA_2019Score17.17—Unverified
6COMET-QEScore16.8—Unverified
7COMET-22Score16.31—Unverified
8UniTE-srcScore15.68—Unverified
9UniTE-refScore15.38—Unverified
10metricx_xxl_DA_2019Score15.24—Unverified