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Don't Blame the Data, Blame the Model: Understanding Noise and Bias When
  Learning from Subjective Annotations

Don't Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations

6 March 2024
Abhishek Anand
Negar Mokhberian
Prathyusha Naresh Kumar
Anweasha Saha
Zihao He
Ashwin Rao
Fred Morstatter
Kristina Lerman
ArXivPDFHTML

Papers citing "Don't Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations"

3 / 3 papers shown
Title
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations
David Tschirschwitz
Volker Rodehorst
18
1
0
14 Sep 2024
Agreeing to Disagree: Annotating Offensive Language Datasets with
  Annotators' Disagreement
Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement
Elisa Leonardelli
Stefano Menini
Alessio Palmero Aprosio
Marco Guerini
Sara Tonelli
45
97
0
28 Sep 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
1