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 2951–3000 of 10752 papers

TitleStatusHype
DISLOG: A logic-based language for processing discourse structures—0
Dissecting In-Context Learning of Translations in GPTs—0
Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation—0
Positioning yourself in the maze of Neural Text Generation: A Task-Agnostic Survey—0
Dissecting the Practical Lexical Function Model for Compositional Distributional Semantics—0
Distance-based Self-Attention Network for Natural Language Inference—0
Distantly Supervised POS Tagging of Low-Resource Languages under Extreme Data Sparsity: The Case of Hittite—0
Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation—0
Improving Word Embedding Factorization for Compression Using Distilled Nonlinear Neural Decomposition—0
Distilled embedding: non-linear embedding factorization using knowledge distillation—0
Creating and using large monolingual parallel corpora for sentential paraphrase generation—0
Distilling Multiple Domains for Neural Machine Translation—0
Better Uncertainty Quantification for Machine Translation Evaluation—0
An Evaluation of Two Vocabulary Reduction Methods for Neural Machine Translation—0
Creating a massively parallel Bible corpus—0
Attention for Implicit Discourse Relation Recognition—0
Distinguishing Degrees of Compositionality in Compound Splitting for Statistical Machine Translation—0
Distinguishing Japanese Non-standard Usages from Standard Ones—0
Distinguishing Literal and Non-Literal Usage of German Particle Verbs—0
Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach—0
DISTO: Evaluating Textual Distractors for Multi-Choice Questions using Negative Sampling based Approach—0
Distortion Model Considering Rich Context for Statistical Machine Translation—0
A Comparative Study of Text Retrieval Models on DaReCzech—0
Distributed representation and estimation of WFST-based n-gram models—0
Distributed Representations for Unsupervised Semantic Role Labeling—0
D-PAGE: Diverse Paraphrase Generation—0
Distributional Properties of Subword Regularization—0
Dive deeper: Deep Semantics for Sentiment Analysis—0
Attention Forcing for Sequence-to-sequence Model Training—0
Divergences in English-Hindi Parallel Dependency Treebanks—0
CREAMT: Creativity and narrative engagement of literary texts translated by translators and NMT—0
Addressing the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts—0
Diverse Words, Shared Meanings: Statistical Machine Translation for Paraphrase, Grounding, and Intent—0
Diversifiable Bootstrapping for Acquiring High-Coverage Paraphrase Resource—0
Diversity and Language Technology: How Techno-Linguistic Bias Can Cause Epistemic Injustice—0
Diversity by Phonetics and its Application in Neural Machine Translation—0
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter—0
Diversity in Machine Learning—0
CRAT: A Multi-Agent Framework for Causality-Enhanced Reflective and Retrieval-Augmented Translation with Large Language Models—0
Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models—0
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation—0
Analysing Coreference in Transformer Outputs—0
DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)—0
DLS@CU at SemEval-2016 Task 1: Supervised Models of Sentence Similarity—0
DLS@CU: Sentence Similarity from Word Alignment and Semantic Vector Composition—0
DLS@CU: Sentence Similarity from Word Alignment—0
DM-CT: Consistency Training with Data and Model Perturbation—0
DMDTEval: An Evaluation and Analysis of LLMs on Disambiguation in Multi-domain Translation—0
Do all Roads Lead to Rome? Understanding the Role of Initialization in Iterative Back-Translation—0
Doubly Attentive Transformer 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