9 citations · 21 across the 8 of their papers we have counts for
8 papers
YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus
David Uthus, Garrett Tanzer, Manfred Georg
Machine learning for sign languages is bottlenecked by data. In this paper, we present YouTube-ASL, a large-scale, open-domain corpus of American Sign Language (ASL) videos and acc…
mLongT5: A Multilingual and Efficient Text-To-Text Transformer for Longer Sequences
David Uthus, Santiago Ontañón, Joshua Ainslie +1
We present our work on developing a multilingual, efficient text-to-text transformer that is suitable for handling long inputs. This model, called mLongT5, builds upon the architec…
CoLT5: Faster Long-Range Transformers with Conditional Computation
Joshua Ainslie, Tao Lei, Michiel de Jong +9
Many natural language processing tasks benefit from long inputs, but processing long documents with Transformers is expensive -- not only due to quadratic attention complexity but…
RISE: Leveraging Retrieval Techniques for Summarization Evaluation
David Uthus, Jianmo Ni
Evaluating automatically-generated text summaries is a challenging task. While there have been many interesting approaches, they still fall short of human evaluations. We present R…
LongT5: Efficient Text-To-Text Transformer for Long Sequences
Mandy Guo, Joshua Ainslie, David Uthus +4
Recent work has shown that either (1) increasing the input length or (2) increasing model size can improve the performance of Transformer-based neural models. In this paper, we pre…
Augmenting Poetry Composition with Verse by Verse
David Uthus, Maria Voitovich, R. J. Mical
We describe Verse by Verse, our experiment in augmenting the creative process of writing poetry with an AI. We have created a group of AI poets, styled after various American class…
Investigating Societal Biases in a Poetry Composition System
Emily Sheng, David Uthus
There is a growing collection of work analyzing and mitigating societal biases in language understanding, generation, and retrieval tasks, though examining biases in creative tasks…
TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restyling
Parker Riley, Noah Constant, Mandy Guo +3
We present a novel approach to the problem of text style transfer. Unlike previous approaches requiring style-labeled training data, our method makes use of readily-available unlab…