causal-tracing

What problem does it solve?

Causal tracing identifies which intermediate computations causally mediate the relationship between inputs and outputs, revealing not just what correlates with behavior but what causes it.

Core Features & Use Cases

• Three Types of Causal Effects: total, direct, and indirect effects, plus the interchange intervention for testing causal relationships across runs.
• Position- and layer-specific tracing: diagnose how different tokens and network layers contribute to final predictions.
• Use cases include debugging model behavior, validating hypotheses about information flow, and guiding interventions to alter outputs.

Quick Start

Run a tracing session on a language model with base and source prompts to compute total, direct, and indirect causal effects.