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LINGO : Visually Debiasing Natural Language Instructions to Support Task
  Diversity

LINGO : Visually Debiasing Natural Language Instructions to Support Task Diversity

12 April 2023
Anjana Arunkumar
Shubham Sharma
Rakhi Agrawal
Sriramakrishnan Chandrasekaran
Chris Bryan
ArXivPDFHTML

Papers citing "LINGO : Visually Debiasing Natural Language Instructions to Support Task Diversity"

3 / 3 papers shown
Title
PromptSource: An Integrated Development Environment and Repository for
  Natural Language Prompts
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts
Stephen H. Bach
Victor Sanh
Zheng-Xin Yong
Albert Webson
Colin Raffel
...
Khalid Almubarak
Xiangru Tang
Dragomir R. Radev
Mike Tian-Jian Jiang
Alexander M. Rush
VLM
225
338
0
02 Feb 2022
Are We Modeling the Task or the Annotator? An Investigation of Annotator
  Bias in Natural Language Understanding Datasets
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets
Mor Geva
Yoav Goldberg
Jonathan Berant
242
320
0
21 Aug 2019
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
190
576
0
02 May 2018
1