Chain of Thought Analysis and Faithfulness

Chain of Thought Analysis

Understanding when and how chain of thought reasoning is faithful to actual model computation.

Core Concepts

• Faithfulness: Whether CoT actually reflects model reasoning
• Post-hoc Rationalization: When models generate plausible but unfaithful explanations
• Causal Influence: Testing if CoT steps causally affect outputs
• Manipulation: How CoT can be used to influence model behavior

Analysis Techniques

• Perturbation studies on reasoning chains
• Comparing CoT with internal activations
• Testing consistency across problem variations
• Measuring correlation with model confidence

Improvement Methods

• Training for faithful reasoning
• Reinforcement learning on verified chains
• Multi-step verification procedures
• Combining with interpretability tools