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.

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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

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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-