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

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Showing 3201–3250 of 10752 papers

TitleStatusHype
Towards User-Driven Neural Machine TranslationCode0
Assessing the Effectiveness of Syntactic Structure to Learn Code Edit RepresentationsCode0
Semi-Supervised and Unsupervised Sense Annotation via Translations—0
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS—0
Exploring Unsupervised Pretraining Objectives for Machine TranslationCode0
Input Augmentation Improves Constrained Beam Search for Neural Machine Translation: NTT at WAT 2021—0
Order-Agnostic Cross Entropy for Non-Autoregressive Machine TranslationCode1
Bayesian Attention Belief Networks—0
AUGVIC: Exploiting BiText Vicinity for Low-Resource NMT—0
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study—0
Self-supervised and Supervised Joint Training for Resource-rich Machine Translation—0
Lexicon Learning for Few-Shot Neural Sequence ModelingCode1
Multilingual Neural Semantic Parsing for Low-Resourced LanguagesCode0
BERTGEN: Multi-task Generation through BERTCode1
On the Language Coverage Bias for Neural Machine Translation—0
Encouraging Neural Machine Translation to Satisfy Terminology Constraints—0
CAPE: Encoding Relative Positions with Continuous Augmented Positional EmbeddingsCode1
Structured Reordering for Modeling Latent Alignments in Sequence TransductionCode1
Itihasa: A large-scale corpus for Sanskrit to English translation—0
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine TranslationCode1
Meaning Representation of Numeric Fused-Heads in UCCA—0
Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings—0
BERTTune: Fine-Tuning Neural Machine Translation with BERTScore—0
AdvPicker: Effectively Leveraging Unlabeled Data via Adversarial Discriminator for Cross-Lingual NERCode0
Cross-language Sentence Selection via Data Augmentation and Rationale Training—0
Scalable Transformers for Neural Machine Translation—0
nmT5 -- Is parallel data still relevant for pre-training massively multilingual language models?—0
Defending Against Backdoor Attacks in Natural Language GenerationCode1
Luna: Linear Unified Nested AttentionCode1
Lightweight Adapter Tuning for Multilingual Speech TranslationCode1
Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine TranslationCode1
How Vision Affects Language: Comparing Masked Self-Attention in Uni-Modal and Multi-Modal Transformer—0
The REPU CS’ Spanish–Quechua Submission to the AmericasNLP 2021 Shared Task on Open Machine Translation—0
Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution)—0
Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas—0
Highland Puebla Nahuatl Speech Translation Corpus for Endangered Language Documentation—0
Feature-level Incongruence Reduction for Multimodal Translation—0
Moses and the Character-Based Random Babbling Baseline: CoAStaL at AmericasNLP 2021 Shared Task—0
Restoring the Sister: Reconstructing a Lexicon from Sister Languages using Neural Machine TranslationCode0
Towards a First Automatic Unsupervised Morphological Segmentation for Inuinnaqtun—0
NRC-CNRC Machine Translation Systems for the 2021 AmericasNLP Shared Task—0
Peru is Multilingual, Its Machine Translation Should Be Too?Code0
Low-Resource Machine Translation Using Cross-Lingual Language Model Pretraining—0
Translate and Classify: Improving Sequence Level Classification for English-Hindi Code-Mixed DataCode0
IITP-MT at CALCS2021: English to Hinglish Neural Machine Translation using Unsupervised Synthetic Code-Mixed Parallel Corpus—0
Using Confidential Data for Domain Adaptation of Neural Machine TranslationCode0
Gated Convolutional Sequence to Sequence Based Learning for English-Hingilsh Code-Switched Machine Translation.—0
Findings of the Second Workshop on Automatic Simultaneous Translation—0
CoMeT: Towards Code-Mixed Translation Using Parallel Monolingual SentencesCode0
On Randomized Classification Layers and Their Implications in Natural Language Generation—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