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 6501–6550 of 10752 papers

TitleStatusHype
First Steps in Using Word Senses as Contextual Features in Maxent Models for Machine Translation—0
First Steps Towards Coverage-Based Document Alignment—0
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models—0
Five Shades of Noise: Analyzing Machine Translation Errors in User-Generated Text—0
Fixed Encoder Self-Attention Patterns in Transformer-Based Machine Translation—0
Fixed-Point Back-Propagation Training—0
Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing—0
Fixing MoE Over-Fitting on Low-Resource Languages in Multilingual Machine Translation—0
FJWU Participation for the WMT21 Biomedical Translation Task—0
FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation—0
Flexible and Efficient Hypergraph Interactions for Joint Hierarchical and Forest-to-String Decoding—0
Flexible Customization of a Single Neural Machine Translation System with Multi-dimensional Metadata Inputs—0
Flexible Non-Autoregressive Neural Machine Translation via Repositioning Edit Operations—0
Florenz: Scaling Laws for Systematic Generalization in Vision-Language Models—0
Flow-Adapter Architecture for Unsupervised Machine Translation—0
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering—0
Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT—0
FLuRKA: Fast and accurate unified Low-Rank & Kernel Attention—0
Flux d’informations dans les systèmes encodeur-décodeur. Application à l’explication des biais de genre dans les systèmes de traduction automatique. (Information flow in encoder-decoder systems applied to the explanation of gender bias in machine translation systems)—0
Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation—0
Focus on the Target’s Vocabulary: Masked Label Smoothing for Machine Translation—0
FooTweets: A Bilingual Parallel Corpus of World Cup Tweets—0
Forced Derivations for Hierarchical Machine Translation—0
Forced Derivation Tree based Model Training to Statistical Machine Translation—0
Forecasting future action sequences with attention: a new approach to weakly supervised action forecasting—0
Foreebank: Syntactic Analysis of Customer Support Forums—0
Foreign Words and the Automatic Processing of Arabic Social Media Text Written in Roman Script—0
Forest-Based Neural Machine Translation—0
Forest Reranking through Subtree Ranking—0
Forest-to-String SMT for Asian Language Translation: NAIST at WAT 2014—0
Formal Basis of a Language Universal—0
Formalising the Swedish Constructicon in Grammatical Framework—0
Formalization of Speech Verbs with NooJ for Machine Translation: the French Verb accuser—0
Formemes in English-Czech Deep Syntactic MT—0
Forming Trees with Treeformers—0
FourierNAT: A Fourier-Mixing-Based Non-Autoregressive Transformer for Parallel Sequence Generation—0
Fourteen Light Tasks for comparing Analogical and Phrase-based Machine Translation—0
Frame-Based Annotation of Multimodal Corpora: Tracking (A)Synchronies in Meaning Construction—0
FrameNet Annotations Alignment using Attention-based Machine Translation—0
Free/Open Source Shallow-Transfer Based Machine Translation for Spanish and Aragonese—0
FreeTransfer-X: Safe and Label-Free Cross-Lingual Transfer from Off-the-Shelf Models—0
Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation—0
Freezing the Pivot for Triangular Machine Translation—0
Frequency-Aware Contrastive Learning for Neural Machine Translation—0
From a Distance: Using Cross-lingual Word Alignments for Noun Compound Bracketing—0
From All Possible Worlds to Small Worlds: A Story of How We Started and Where We Will Go Doing Semantics—0
From Bilingual to Multilingual Neural Machine Translation by Incremental Training—0
From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation—0
From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks—0
From dictations to clinical reports using machine translation—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
5AdminBLEU score43.8—Unverified
6Transformer (ADMIN init)BLEU 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