2 citations · 5 across the 4 of their papers we have counts for
4 papers
In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workers
Vivek Krishna Pradhan, Mike Schaekermann, Matthew Lease
We propose a novel three-stage FIND-RESOLVE-LABEL workflow for crowdsourced annotation to reduce ambiguity in task instructions and thus improve annotation quality. Stage 1 (FIND)…
Proceedings of the CSCW 2021 Workshop -- Investigating and Mitigating Biases in Crowdsourced Data
Danula Hettiachchi, Mark Sanderson, Jorge Goncalves +5
This volume contains the position papers presented at CSCW 2021 Workshop - Investigating and Mitigating Biases in Crowdsourced Data, held online on 23rd October 2021, at the 24th A…
Data Excellence for AI: Why Should You Care
Lora Aroyo, Matthew Lease, Praveen Paritosh +1
The efficacy of machine learning (ML) models depends on both algorithms and data. Training data defines what we want our models to learn, and testing data provides the means by whi…
The Challenge of Variable Effort Crowdsourcing and How Visible Gold Can Help
Danula Hettiachchi, Mike Schaekermann, Tristan McKinney +1
We consider a class of variable effort human annotation tasks in which the number of labels required per item can greatly vary (e.g., finding all faces in an image, named entities…