Which category includes techniques such as few-shot, zero-shot, tree-of-thought (ToT), chain-of-thought (CoT), and self-consistency?

Which category includes techniques such as few-shot, zero-shot, tree-of-thought (ToT), chain-of-thought (CoT), and self-consistency?

• A. Advanced Prompting Technique
• B. Bias
• C. Ethics
• D. Structured Prompts

Answer: (A)

These techniques are all examples of Advanced prompting techniques, ways to design prompts that guide a model to reason more effectively and produce better results. Few-shot prompting introduces a few example problems and solutions in the prompt to set a pattern the model should follow. Zero-shot prompting relies on giving instructions without examples, testing the model’s general capabilities. Chain-of-thought prompting explicitly asks the model to lay out intermediate reasoning steps before giving the final answer, which helps with complex tasks and makes the reasoning process observable. Tree-of-thought broadens that idea by encouraging a structured exploration of multiple reasoning paths to find a robust solution. Self-consistency takes a different angle by generating multiple possible reasoning paths and choosing the most common or consistent final result, improving reliability. These techniques share the goal of steering how the model reasons and answers through prompt design, rather than addressing biases, ethics, or simply applying a fixed, rigid template. That’s why the appropriate category is Advanced prompting techniques.

These techniques are all examples of Advanced prompting techniques, ways to design prompts that guide a model to reason more effectively and produce better results. Few-shot prompting introduces a few example problems and solutions in the prompt to set a pattern the model should follow. Zero-shot prompting relies on giving instructions without examples, testing the model’s general capabilities. Chain-of-thought prompting explicitly asks the model to lay out intermediate reasoning steps before giving the final answer, which helps with complex tasks and makes the reasoning process observable. Tree-of-thought broadens that idea by encouraging a structured exploration of multiple reasoning paths to find a robust solution. Self-consistency takes a different angle by generating multiple possible reasoning paths and choosing the most common or consistent final result, improving reliability.

These techniques share the goal of steering how the model reasons and answers through prompt design, rather than addressing biases, ethics, or simply applying a fixed, rigid template. That’s why the appropriate category is Advanced prompting techniques.