Diagnosing and Correcting RAG System Output
A Retrieval-Augmented Generation (RAG) system is designed to answer customer questions based on a company's knowledge base. Analyze the following interaction. Based on the provided instruction, context, and the model's output, identify the flaw in the system's instruction and explain how you would change it to produce a more helpful and accurate response.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Evaluation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Using Pre-trained Knowledge when Retrieved Context is Insufficient
Restricting LLM Answers to Provided Text
A team is developing a question-answering system for a company's internal, highly-accurate technical manuals. The system's highest priority is to ensure that all answers are strictly based on the information found within these manuals and to avoid generating any information from its general knowledge. Given a user's question and a relevant passage retrieved from the manuals, which of the following instructions to the language model would be most effective at achieving this goal?
Diagnosing and Correcting RAG System Output
Evaluating Prompt Strategy for a Creative RAG Task