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State of Machine Translation | Report | ScienceToStartup
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Machine Translation
State of Machine Translation
15 papers · avg viability 5.9
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Top papers
From Words to Worlds: Benchmarking Cross-Cultural Cultural Understanding in Machine Translation
(8.0)
Omnilingual MT: Machine Translation for 1,600 Languages
(8.0)
Cross-Preference Learning for Sentence-Level and Context-Aware Machine Translation
(7.0)
Samasāmayik: A Parallel Dataset for Hindi-Sanskrit Machine Translation
(7.0)
Domain-Specific Quality Estimation for Machine Translation in Low-Resource Scenarios
(7.0)
Is Human Annotation Necessary? Iterative MBR Distillation for Error Span Detection in Machine Translation
(7.0)
Large Language Models as Annotators for Machine Translation Quality Estimation
(7.0)
Unlocking Reasoning Capability on Machine Translation in Large Language Models
(6.0)
Towards Reliable Machine Translation: Scaling LLMs for Critical Error Detection and Safety
(5.0)
Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAG
(5.0)
Developing an English-Efik Corpus and Machine Translation System for Digitization Inclusion
(5.0)
Machine Translation in the Wild: User Reaction to Xiaohongshu's Built-In Translation Feature
(4.0)
Enhancing Document-Level Machine Translation via Filtered Synthetic Corpora and Two-Stage LLM Adaptation
(4.0)
Translation or Recitation? Calibrating Evaluation Scores for Machine Translation of Extremely Low-Resource Languages
(4.0)
Bidirectional Chinese and English Passive Sentences Dataset for Machine Translation
(4.0)
