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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 1351–1400 of 10752 papers

TitleStatusHype
Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine TranslationCode0
Extrapolating Multilingual Understanding Models as Multilingual Generators—0
Machine Translation by Projecting Text into the Same Phonetic-Orthographic Space Using a Common Encoding—0
Is Translation Helpful? An Empirical Analysis of Cross-Lingual Transfer in Low-Resource Dialog Generation—0
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages—0
Communication Efficient Federated Learning for Multilingual Neural Machine Translation with AdapterCode1
Explaining How Transformers Use Context to Build PredictionsCode1
Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene HallucinationCode1
AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech TranslationCode0
Viewing Knowledge Transfer in Multilingual Machine Translation Through a Representational Lens—0
Pseudo-Label Training and Model Inertia in Neural Machine Translation—0
DUB: Discrete Unit Back-translation for Speech TranslationCode1
The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics—0
Cross-Lingual Supervision improves Large Language Models Pre-training—0
ReSeTOX: Re-learning attention weights for toxicity mitigation in machine translationCode0
HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine TranslationCode2
Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plants—0
Multilingual Event Extraction from Historical Newspaper AdvertsCode0
Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting ModelCode0
Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel CorpusCode1
On the Off-Target Problem of Zero-Shot Multilingual Neural Machine TranslationCode0
NollySenti: Leveraging Transfer Learning and Machine Translation for Nigerian Movie Sentiment ClassificationCode0
Bring More Attention to Syntactic Symmetry for Automatic Postediting of High-Quality Machine Translations—0
ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time—0
Searching for Needles in a Haystack: On the Role of Incidental Bilingualism in PaLM's Translation Capability—0
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages—0
Variable-length Neural Interlingua Representations for Zero-shot Neural Machine Translation—0
Accelerating Transformer Inference for Translation via Parallel DecodingCode3
Epsilon Sampling Rocks: Investigating Sampling Strategies for Minimum Bayes Risk Decoding for Machine TranslationCode1
A Survey on Zero Pronoun Translation—0
AR-Diffusion: Auto-Regressive Diffusion Model for Text GenerationCode1
Iterative Adversarial Attack on Image-guided Story Ending Generation—0
xPQA: Cross-Lingual Product Question Answering across 12 LanguagesCode1
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech TranslationCode0
Exploring the Impact of Layer Normalization for Zero-shot Neural Machine Translation—0
Progressive Translation: Improving Domain Robustness of Neural Machine Translation with Intermediate SequencesCode0
Critical Appraisal of Artificial Intelligence-Mediated Communication—0
Understanding and Bridging the Modality Gap for Speech TranslationCode1
Back Translation for Speech-to-text Translation Without TranscriptsCode1
Towards Understanding and Improving Knowledge Distillation for Neural Machine TranslationCode0
RC3: Regularized Contrastive Cross-lingual Cross-modal Pre-trainingCode0
PESTS: Persian_English Cross Lingual Corpus for Semantic Textual Similarity—0
Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine TranslationCode0
Improving Cascaded Unsupervised Speech Translation with Denoising Back-translation—0
Improving the Quality of Neural Machine Translation Through Proper Translation of Name Entities—0
Improving Zero-shot Multilingual Neural Machine Translation by Leveraging Cross-lingual Consistency RegularizationCode1
How Good are Commercial Large Language Models on African Languages?—0
Chain-of-Dictionary Prompting Elicits Translation in Large Language ModelsCode0
Subword Segmental Machine Translation: Unifying Segmentation and Target Sentence GenerationCode0
The First Parallel Corpora for Kurdish Sign Language—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