利用语义关联增强的跨语言预训练模型的译文质量评估(A Cross-language Pre-trained Model with Enhanced Semantic Connection for MT Quality Estimation)

No abstract is available for this paper.

• Publication year

  2021

• Venue

  China National Conference on Chinese Computational Linguistics

• Publication date

  Unknown publication date

• Fields of study

  Not labeled

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• DirectQE: Direct Pretraining for Machine Translation Quality Estimation

  2021cited by this paper
• Quality In, Quality Out: Learning from Actual Mistakes

  2020cited by this paper
• Intermediate Self-supervised Learning for Machine Translation Quality Estimation

  2020cited by this paper
• Improved Quality Estimation of Machine Translation with Pre-trained Language Representation

  2019cited by this paper
• Findings of the WMT 2019 Shared Tasks on Quality Estimation

  2019cited by this paper
• QE BERT: Bilingual BERT Using Multi-task Learning for Neural Quality Estimation

  2019cited by this paper
• NJU Submissions for the WMT19 Quality Estimation Shared Task

  2019cited by this paper
• SOURCE: SOURce-Conditional Elmo-style Model for Machine Translation Quality Estimation

  2019cited by this paper
• RoBERTa: A Robustly Optimized BERT Pretraining Approach

  2019cited by this paper
• What Does BERT Learn about the Structure of Language?

  2019cited by this paper
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

  2019cited by this paper
• Unsupervised Cross-lingual Representation Learning at Scale

  2019cited by this paper
• deepQuest: A Framework for Neural-based Quality Estimation

  2018cited by this paper
• "Bilingual Expert" Can Find Translation Errors

  2018cited by this paper
• A Unified Neural Network for Quality Estimation of Machine Translation

  2018cited by this paper
• Pushing the Limits of Translation Quality Estimation

  2017cited by this paper
• Attention is All you Need

  2017cited by this paper
• Predictor-Estimator using Multilevel Task Learning with Stack Propagation for Neural Quality Estimation

  2017cited by this paper
• Fixing Weight Decay Regularization in Adam

  2017influential reference
• Neural Machine Translation of Rare Words with Subword Units

  2015cited by this paper
• Sequence to Sequence Learning with Neural Networks

  2014cited by this paper
• QuEst - A translation quality estimation framework

  2013cited by this paper
• METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments

  2005cited by this paper
• ROUGE: A Package for Automatic Evaluation of Summaries

  2004cited by this paper
• Confidence Estimation for Machine Translation

  2004cited by this paper
• Bleu: a Method for Automatic Evaluation of Machine Translation

  2002cited by this paper
• Motivations

  2000cited by this paper

• No citing papers are available for this paper.