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Survey on Learning from Disagreement in AI by annarhysa.a2020 is a document available to read on EtoBox.

What is Survey on Learning from Disagreement in AI about?

The document is a survey on learning from disagreement in Natural Language Processing (NLP) and Computer Vision (CV), highlighting that human disagreement is common in annotation tasks, challenging the assumption of a single correct interpretation. It reviews various approaches to training models using datasets with multiple judgments and emphasizes the importance of evaluation methods and dataset characteristics on model performance. The findings suggest that leveraging soft labels can improve results, par

Author

annarhysa.a2020

Language

EN