Improving a Faulty Retrieval-Augmented Chatbot
Based on the provided case study, outline a comprehensive, two-part strategy to address the chatbot's failures. For each part of your strategy, describe its primary goal and explain why implementing only one of the two approaches would be a less robust solution.
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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
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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Enhancing LLM Faithfulness and Robustness via Prompting
Improving a Faulty Retrieval-Augmented Chatbot
A team developing a Retrieval-Augmented Generation (RAG) system for a legal database finds that it occasionally generates incorrect legal interpretations. This happens when the system retrieves legal documents that are either irrelevant to the user's query or outdated. The team decides to implement a two-part solution. Which of the following options best exemplifies the dual-approach strategy for handling this inaccurate retrieval?
Improving Retrieval Accuracy in RAG
A team is working to reduce incorrect outputs from their Retrieval-Augmented Generation (RAG) system, which are caused by flawed retrieved documents. Match each of the two primary strategies they can employ with its corresponding description and goal.