269 citations · 646 across the 18 of their papers we have counts for
4 papers · 1 filter
Data Weighted Training Strategies for Grammatical Error Correction
Jared Lichtarge, Chris Alberti, Shankar Kumar
Recent progress in the task of Grammatical Error Correction (GEC) has been driven by addressing data sparsity, both through new methods for generating large and noisy pretraining d…
QED: A Framework and Dataset for Explanations in Question Answering
Matthew Lamm, Jennimaria Palomaki, Chris Alberti +4
A question answering system that in addition to providing an answer provides an explanation of the reasoning that leads to that answer has potential advantages in terms of debuggab…
Big Bird: Transformers for Longer Sequences
Manzil Zaheer, Guru Guruganesh, Avinava Dubey +8
Transformers-based models, such as BERT, have been one of the most successful deep learning models for NLP. Unfortunately, one of their core limitations is the quadratic dependency…
ETC: Encoding Long and Structured Inputs in Transformers
Joshua Ainslie, Santiago Ontanon, Chris Alberti +7
Transformer models have advanced the state of the art in many Natural Language Processing (NLP) tasks. In this paper, we present a new Transformer architecture, Extended Transforme…