Series 2: Meta-Cognitive Techniques
This series explores meta-cognitive approaches that teach LLMs to think about their own thinking processes and improve their reasoning quality.
Articles in This Series
- Article 36: Meta-Cognition Prompting: Teaching Models to Think About Thinking
- Article 37: Self-Skepticism Reinforcement: Building Critical Thinking
- Article 38: Adversarial Self-Critique: Improving Through Opposition
- Article 39: Iterative Contradiction Resolution: Resolving Conflicts
- Article 40: Cognitive Dissonance Induction: Forcing Deeper Analysis
Series Overview
This series delves into meta-cognitive techniques that enhance LLMs' ability to monitor and improve their own thinking processes. We'll explore methods for building critical thinking, self-evaluation, and iterative improvement in AI reasoning.
Learning Objectives
By the end of this series, you will:
- Understand meta-cognitive prompting techniques
- Know how to build self-skepticism and critical thinking
- Be able to implement adversarial self-critique
- Understand iterative contradiction resolution
- Know how to induce cognitive dissonance for deeper analysis
Prerequisites
- Completion of Series 1: Reasoning and Thinking Patterns
- Understanding of advanced reasoning techniques
- Experience with complex reasoning tasks