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GRASP: A Disagreement Analysis Framework to Assess Group Associations in Perspectives

Human annotation plays a core role in machine learning — annotations for supervised models, safety guardrails for generative models, and human feedback for reinforcement learning, to cite a few avenues. However, the fact that many of these human annotations are inherently subjective is often overlooked.

Data and Resources

Cite this as

Vinodkumar Prabhakaran, Christopher M. Homan, Lora Aroyo, Aida Mostafazadeh Davani, Alicia Parrish, Alex Taylor, Mark Díaz, Ding Wang, Gregory Serapio-García (2024). Dataset: GRASP: A Disagreement Analysis Framework to Assess Group Associations in Perspectives. https://doi.org/10.57702/hlmr55n3

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2311.05074
Author Vinodkumar Prabhakaran
More Authors
Christopher M. Homan
Lora Aroyo
Aida Mostafazadeh Davani
Alicia Parrish
Alex Taylor
Mark Díaz
Ding Wang
Gregory Serapio-García
Homepage https://github.com/google-research-datasets/dices-