Improving Chatbot Responses on a Budget
A small e-commerce company uses a general-purpose language model for its customer service chatbot. While the model is good at understanding queries, its responses are often too generic and sometimes factually incorrect about the company's specific products. The company does not have the budget or technical expertise to perform extensive retraining or fine-tuning on the large model.
Based on this scenario, propose a cost-effective, inference-time strategy to improve the quality of the chatbot's final responses. Describe the two main components your system would need and how they would interact to select a better answer from multiple generated options.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Ch.5 Inference - Foundations of Large Language Models
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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Improving Chatbot Responses on a Budget
A system is designed to improve the quality of its generated responses at inference time without altering the base model's parameters. It does this by producing several options and then choosing the best one. Arrange the following actions into the correct operational sequence.