Datasets › AGGA: A Dataset of Academic Guidelines for Generative AIs
AGGA: A Dataset of Academic Guidelines for Generative AIs
AGGA (Academic Guidelines for Generative AIs) is a dataset of 80 academic guidelines for the usage of generative AIs and large language models in academia, selected systematically and collected from official university websites across six continents. Comprising 181,225 words, the dataset supports natural language processing tasks such as language modeling, sentiment and semantic analysis, model synthesis, classification, and topic labeling. It can also serve as a benchmark for ambiguity detection and requirements categorization. This resource aims to facilitate research on AI governance in educational contexts, promoting a deeper understanding of the integration of AI technologies in academia.
Benchmarks archive 2025-07-28
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Papers archive 2025-07-28
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Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
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Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- AGGA: A Dataset of Academic Guidelines for Generative AIs
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