Enhancing agronomic advisory in East Africa through integration of domain- Adapted Large Language Models (LLMs) and existing data-driven frameworks.
This study explores how integration of domain-adapted Large Language Models (LLMs) and existing data-driven frameworks enhance wheat agronomic advisory services in east Africa. Although LLMs hold transformative potential across various domains, their use in agro-advisory services in resource-constra...
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| Format: | Tesis |
| Language: | Inglés |
| Published: |
2025
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| Online Access: | https://hdl.handle.net/10568/176138 |
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