430 citations · 481 across the 7 of their papers we have counts for
10 papers · 1 filter
Query Refinement Prompts for Closed-Book Long-Form Question Answering
Reinald Kim Amplayo, Kellie Webster, Michael Collins +2
Large language models (LLMs) have been shown to perform well in answering questions and in producing long-form texts, both in few-shot closed-book settings. While the former can be…
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…
Measuring and Reducing Gendered Correlations in Pre-trained Models
Kellie Webster, Xuezhi Wang, Ian Tenney +6
Pre-trained models have revolutionized natural language understanding. However, researchers have found they can encode artifacts undesired in many applications, such as professions…
Type B Reflexivization as an Unambiguous Testbed for Multilingual Multi-Task Gender Bias
Ana Valeria Gonzalez, Maria Barrett, Rasmus Hvingelby +2
The one-sided focus on English in previous studies of gender bias in NLP misses out on opportunities in other languages: English challenge datasets such as GAP and WinoGender highl…