SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5201–5250 of 10752 papers

TitleStatusHype
Response-based Learning for Machine Translation of Open-domain Database Queries—0
Responsible Multilingual Large Language Models: A Survey of Development, Applications, and Societal Impact—0
ResSim at SemEval-2017 Task 1: Multilingual Word Representations for Semantic Textual Similarity—0
Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation—0
Restricted or Not: A General Training Framework for Neural Machine Translation—0
Results from the ML4HMT-12 Shared Task on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid Machine Translation—0
Results of the WMT13 Metrics Shared Task—0
Results of the WMT14 Metrics Shared Task—0
Results of the WMT15 Metrics Shared Task—0
Results of the WMT15 Tuning Shared Task—0
Results of the WMT16 Metrics Shared Task—0
Results of the WMT16 Tuning Shared Task—0
Results of the WMT17 Metrics Shared Task—0
Results of the WMT17 Neural MT Training Task—0
Results of the WMT18 Metrics Shared Task: Both characters and embeddings achieve good performance—0
Resumptive Pronoun Detection for Modern Standard Arabic to English MT—0
Rethinking Human-like Translation Strategy: Integrating Drift-Diffusion Model with Large Language Models for Machine Translation—0
Rethinking Skip Connection with Layer Normalization in Transformers and ResNets—0
Rethinking Skip Connection with Layer Normalization—0
Rethinking the Design of Sequence-to-Sequence Models for Efficient Machine Translation—0
Digging Errors in NMT: Evaluating and Understanding Model Errors from Partial Hypothesis Space—0
Rethinking Translation Memory Augmented Neural Machine Translation—0
Re-training Monolingual Parser Bilingually for Syntactic SMT—0
Re-translation versus Streaming for Simultaneous Translation—0
Retrieval Term Prediction Using Deep Learning Methods—0
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison—0
Retrosynthesis with Attention-Based NMT Model and Chemical Analysis of the "Wrong" Predictions—0
Return of the RNN: Residual Recurrent Networks for Invertible Sentence Embeddings—0
Reversibility reconsidered: finite-state factors for efficient probabilistic sampling in parsing and generation—0
Reversing Morphological Tokenization in English-to-Arabic SMT—0
Review of coreference resolution in English and Persian—0
Review of Hypothesis Alignment Algorithms for MT System Combination via Confusion Network Decoding—0
Revisit Automatic Error Detection for Wrong and Missing Translation -- A Supervised Approach—0
Revisiting Character-Based Neural Machine Translation with Capacity and Compression—0
Revisiting Checkpoint Averaging for Neural Machine Translation—0
Revisiting Context Choices for Context-aware Machine Translation—0
Revisiting Low Resource Status of Indian Languages in Machine Translation—0
Revisiting Machine Translation for Cross-lingual Classification—0
Revisiting Modularized Multilingual NMT to Meet Industrial Demands—0
Revisiting Neural Scaling Laws in Language and Vision—0
Revisiting Representation Degeneration Problem in Language Modeling—0
Revisiting Robust Neural Machine Translation: A Transformer Case Study—0
Revisiting Syllables in Language Modelling and their Application on Low-Resource Machine Translation—0
Revisiting the Case for Explicit Syntactic Information in Language Models—0
Revisiting the Markov Property for Machine Translation—0
Revitalization of Indigenous Languages through Pre-processing and Neural Machine Translation: The case of Inuktitut—0
Reward Augmented Maximum Likelihood for Neural Structured Prediction—0
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems—0
Rewriter-Evaluator Framework for Neural Machine Translation—0
Rewriter-Evaluator Architecture for Neural Machine Translation—0
Show:102550
← PrevPage 105 of 216Next →
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