430 citations · 784 across the 14 of their papers we have counts for
4 papers · 1 filter
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Nan Du, Yanping Huang, Andrew M. Dai +24
Scaling language models with more data, compute and parameters has driven significant progress in natural language processing. For example, thanks to scaling, GPT-3 was able to ach…
How to Write a Bias Statement: Recommendations for Submissions to the Workshop on Gender Bias in NLP
Christian Hardmeier, Marta R. Costa-jussà, Kellie Webster +2
At the Workshop on Gender Bias in NLP (GeBNLP), we'd like to encourage authors to give explicit consideration to the wider aspects of bias and its social implications. For the 2020…
Toward Deconfounding the Influence of Entity Demographics for Question Answering Accuracy
Maharshi Gor, Kellie Webster, Jordan Boyd-Graber
The goal of question answering (QA) is to answer any question. However, major QA datasets have skewed distributions over gender, profession, and nationality. Despite that skew, mod…
They, Them, Theirs: Rewriting with Gender-Neutral English
Tony Sun, Kellie Webster, Apu Shah +2
Responsible development of technology involves applications being inclusive of the diverse set of users they hope to support. An important part of this is understanding the many wa…