---
license: apache-2.0
tags:
  - mechanistic-interpretability
  - gpt2
  - probing
  - logit-lens
  - activation-patching
language:
  - en
---

# The Champollion Protocol

Deciphering a language model's internal representations using the same method
Champollion used to decipher Egyptian hieroglyphs in 1822.

**Author:** Fabrice Fils-Aimé

## Method

1. **Rosetta Stone** — Factual prompts with known answers, verified against the model
2. **Cartouches** — Hidden-state extraction at every layer
3. **Cross-comparison** — Logit lens to track prediction emergence
4. **Partial alphabet** — Linear probes (5-fold CV) to decode layer-wise information
5. **Coptic validation** — Held-out test set to verify generalization
6. **Mixed system** — Activation patching to identify causal vs structural layers

## Citation

```bibtex
@misc{filsaime2026champollion,
  title={The Champollion Protocol: Deciphering LLM Internal Representations},
  author={Fils-Aim\'e, Fabrice},
  year={2026},
  url={https://huggingface.co/fabthebest/champollion-protocol}
}
```