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Prompting Without Structural Adaptation
Prompting offers a straightforward and effective technique to direct a single Large Language Model to execute various tasks without needing to alter the model's underlying architecture or parameters. However, for this approach to be successful, it is a prerequisite that the language model already has the capacity to comprehend and adhere to the given instructions or questions.
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Foundations of Large Language Models
Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Example of Instruction Following: Summarization
A user provides a language model with the following prompt: 'List the three most common states of matter. Then, in a separate, single sentence, explain why gases do not have a fixed shape.' Which of the following model responses best demonstrates a complete and accurate adherence to the user's instructions?
Evaluating LLM Instruction Adherence
Analyzing an LLM's Instructional Failure
Necessity of Tuning for Instruction Following
Prompting Without Structural Adaptation