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Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning
We present a novel dataset generation process that leads to more effective knowledge ingestion through SFT, and our results show considerable performance improvements in Q&A tasks related to out-of-domain knowledge.
GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models
Our analysis highlights GPT-4's ability to achieve a passing score on exams to earn credits for renewing agronomist certifications, answering 93% of the questions correctly and outperforming earlier general-purpose models, which achieved 88% accuracy.
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