Towards Inclusive, Contextual, and Balanced Agricultural Advisories: Refining GPT-5 Agricultural Advisories for Kenya with Reinforcement Learning from Human Feedback
This study presents a human-in-the-loop framework to enhance the accuracy, inclusivity, and contextual relevance of GPT-5-based agricultural advisories in Kenya. Using over 2,800 real farmer queries from the iShamba SMS platform, researchers applied prompt optimization, expert review, and Reinforcem...
| Main Authors: | , , |
|---|---|
| Format: | Artículo preliminar |
| Language: | Inglés |
| Published: |
Accelerating Impacts of CGIAR Climate Research for Africa
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/177324 |
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