Inter-Annotator Agreement and Its Reflection in LLMs and Responsible AI.
Recent research on Responsible AI, particularly in addressing algorithmic biases, has gained significant attention. Natural Language Processing (NLP) algorithms, which rely on human-generated and human-labeled data, often reflect these challenges. In this paper, we analyze inter-annotator agreement...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2025-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/139049 |
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