arXiv:1803.06535
공식 코드 · Papers with Code
Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer
원문 초록
Style transfer is the task of automatically transforming a piece of text in one particular style into another. A major barrier to progress in this field has been a lack of training and evaluation datasets, as well as benchmarks and automatic metrics. In this work, we create the largest corpus for a particular stylistic transfer (formality) and show that techniques from the machine translation community can serve as strong baselines for future work. We also discuss challenges of using automatic metrics.
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CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
Gender Bias in English-to-Greek Machine Translation
TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration
Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation
Unsupervised Word-level Quality Estimation for Machine Translation Through the Lens of Annotators (Dis)agreement
토론
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