263 citations · 279 across the 4 of their papers we have counts for
4 papers
Finding Replicable Human Evaluations via Stable Ranking Probability
Parker Riley, Daniel Deutsch, George Foster +3
Reliable human evaluation is critical to the development of successful natural language generation models, but achieving it is notoriously difficult. Stability is a crucial require…
Prompting PaLM for Translation: Assessing Strategies and Performance
David Vilar, Markus Freitag, Colin Cherry +3
Large language models (LLMs) that have been trained on multilingual but not parallel text exhibit a remarkable ability to translate between languages. We probe this ability in an i…
DOCmT5: Document-Level Pretraining of Multilingual Language Models
Chia-Hsuan Lee, Aditya Siddhant, Viresh Ratnakar +1
In this paper, we introduce DOCmT5, a multilingual sequence-to-sequence language model pretrained with large scale parallel documents. While previous approaches have focused on lev…
Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation
Markus Freitag, George Foster, David Grangier +3
Human evaluation of modern high-quality machine translation systems is a difficult problem, and there is increasing evidence that inadequate evaluation procedures can lead to erron…