24 citations · 27 across the 4 of their papers we have counts for
4 papers
Using Machine Translation to Localize Task Oriented NLG Output
Scott Roy, Cliff Brunk, Kyu-Young Kim +6
One of the challenges in a task oriented natural language application like the Google Assistant, Siri, or Alexa is to localize the output to many languages. This paper explores doi…
Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study
Dara Bahri, Yi Tay, Che Zheng +3
Large generative language models such as GPT-2 are well-known for their ability to generate text as well as their utility in supervised downstream tasks via fine-tuning. Our work i…
Reverse Engineering Configurations of Neural Text Generation Models
Yi Tay, Dara Bahri, Che Zheng +3
This paper seeks to develop a deeper understanding of the fundamental properties of neural text generations models. The study of artifacts that emerge in machine generated text as…
Multilingual Language Processing From Bytes
Dan Gillick, Cliff Brunk, Oriol Vinyals +1
We describe an LSTM-based model which we call Byte-to-Span (BTS) that reads text as bytes and outputs span annotations of the form [start, length, label] where start positions, len…