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RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Our pipeline consists of multiple stages, including extracting information from PDFs, generating questions and answers, using them for fine-tuning, and leveraging GPT-4 for evaluating the results.
Detecting Out-Of-Distribution Samples Using Low-Order Deep Features Statistics
The ability to detect when an input sample was not drawn from the training distribution is an important desirable property of deep neural networks.
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