Logit lens is the analysis technique that projects intermediate hidden states through the final unembedding to estimate token preferences at each layer - it offers a quick view of how predictions evolve across model depth.

What Is Logit lens?

• Definition: Applies output projection to hidden activations before final layer to inspect provisional logits.
• Interpretation: Shows which candidate tokens are being formed at intermediate computation stages.
• Speed: Provides lightweight diagnostics without full retraining or heavy instrumentation.
• Limitation: Raw projections can be biased because intermediate states are not optimized for direct decoding.

Why Logit lens Matters

• Layer Insight: Helps visualize when key information appears during forward pass.
• Debug Utility: Useful for spotting layer regions where target signal is lost or distorted.
• Education: Provides intuitive interpretability entry point for new researchers.
• Hypothesis Generation: Supports rapid exploration before deeper causal analysis.
• Caution: Results need careful interpretation due to calibration mismatch.

How It Is Used in Practice

• Comparative Use: Compare logit-lens trajectories between successful and failing prompts.
• Token Focus: Track rank and probability shifts for specific expected tokens.
• Validation: Confirm lens-based hypotheses with patching or ablation experiments.

Logit lens is a fast diagnostic lens for intermediate token prediction dynamics - logit lens is valuable for exploration when its projection bias is accounted for in interpretation.