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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 4401–4450 of 10752 papers

TitleStatusHype
Hierarchical Attention Transformer Architecture For Syntactic Spell Correction—0
Non-Autoregressive Image Captioning with Counterfactuals-Critical Multi-Agent Learning—0
Neural Machine Translation for South Africa's Official Languages—0
Learning to Detect Unacceptable Machine Translations for Downstream Tasks—0
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine TranslationCode1
Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine TranslationCode1
On Exposure Bias, Hallucination and Domain Shift in Neural Machine TranslationCode1
Unsupervised Multimodal Neural Machine Translation with Pseudo Visual Pivoting—0
Neural Syntactic Preordering for Controlled Paraphrase GenerationCode1
It's Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual InformationCode1
Evaluating Explanation Methods for Neural Machine Translation—0
Using Context in Neural Machine Translation Training Objectives—0
Dynamic Programming Encoding for Subword Segmentation in Neural Machine TranslationCode1
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation EvaluationCode1
How Does Selective Mechanism Improve Self-Attention Networks?Code1
On the Inference Calibration of Neural Machine TranslationCode1
A Comprehensive Survey of Grammar Error Correction—0
Practical Perspectives on Quality Estimation for Machine Translation—0
Synthesizer: Rethinking Self-Attention in Transformer ModelsCode1
ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine TranslationCode1
Hard-Coded Gaussian Attention for Neural Machine TranslationCode1
Improving Non-autoregressive Neural Machine Translation with Monolingual Data—0
Mirror-Generative Neural Machine Translation—0
Improving Neural Language Generation with Spectrum Control—0
Neural Machine Translation with Universal Visual RepresentationCode1
Data-dependent Gaussian Prior Objective for Language Generation—0
Compositional Language Continual LearningCode1
Exploring the Enrichment of Basque WordNet with a Sentiment Lexicon—0
Utterance-Unit Annotation for the JSL Dialogue Corpus: Toward a Multimodal Approach to Corpus Linguistics—0
Machine Translation from Spoken Language to Sign Language using Pre-trained Language Model as Encoder—0
A French Corpus for Semantic Similarity—0
Improving NMT Quality Using Terminology Injection—0
The Learnability of the Annotated Input in NMT Replicating (Vanmassenhove and Way, 2018) with OpenNMT—0
Collection and Annotation of the Romanian Legal Corpus—0
TDDC: Timely Disclosure Documents Corpus—0
Linguistically Informed Hindi-English Neural Machine Translation—0
Evaluation Dataset for Zero Pronoun in Japanese to English Translation—0
Multilingual Neural Machine Translation involving Indian Languages—0
A Post-Editing Dataset in the Legal Domain: Do we Underestimate Neural Machine Translation Quality?—0
Towards a Spell Checker for Zamboanga Chavacano Orthography—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
Building an English-Chinese Parallel Corpus Annotated with Sub-sentential Translation Techniques—0
A Parallel WordNet for English, Swedish and Bulgarian—0
Paraphrase Generation and Evaluation on Colloquial-Style Sentences—0
The Competitiveness Analysis of the European Language Technology Market—0
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts—0
Methodological Aspects of Developing and Managing an Etymological Lexical Resource: Introducing EtymDB-2.0Code1
Multilingual Dictionary Based Construction of Core Vocabulary—0
Multiword Expression aware Neural Machine Translation—0
Better Together: Modern Methods Plus Traditional Thinking in NP Alignment—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