Research · Results · Experiment
Probe the decision, not the goal.
An interpretability report on Pythagoras-Prover-4B. Read at the moment it chooses a tactic, the prover's next move is linearly encoded mid-network — far beyond what the proof text alone implies.
Headline
The tactic is decided before it is written.
exact when pushed along one direction at layer 16; equal-energy null directions flip 16–18%We froze a trained Lean theorem prover and asked what its activations make linearly readable, with no gradient and no generation. Read from the theorem statement, the prover is barely better than a general text encoder at predicting the tactic: the goal predicts the tactic, and any encoder sees the goal. Read at the decision state — the position just before a tactic is emitted, mid-proof — the prover carries its choice well above the surface, rising with depth through layers 8–20. A single direction in the residual stream then causally steers that choice for exact, simp and have, and fails honestly for apply and rw.
The result, in four pages
Read it, then look at it.
The written report
Question, method, the dissociation table, the depth map, certification, the two corrections, steering, the inscribed classics, and the limits.
Visual · start hereProbe the decision
The goal-versus-decision flip side by side, accuracy through depth, the site map, and the exact-width raster of raw activations you can slice yourself.
Visual · proofsProof reader
57 recognisable theorems the prover actually proved — Wilson, Euclid's lemma, Fermat's little theorem, Cauchy–Schwarz — read line by line, with the layer where each tactic commits and the steering panel.
Visual · activationsActivation manifolds
The geometry of a proof concept in three dimensions: domain and decision-state activations in the whitened metric, prover against general encoder.
The model
What was measured, on what.
| Model | Pythagoras-LM/Pythagoras-Prover-4B on Hugging Face — a Qwen3-4B derivative, 36 layers, hidden size 2560, run dense in fp32 |
| Pinned revision | aa05cf9a86cd1bc5af16935ab8f2190f4a1e62b8 |
| Corpus | The QED Lean-proof corpus; tactic labels come from the winning, compiled proofs in the proven ledger |
| Method | Option G: probe, classify and complete a concept family on frozen activations. Whitened linear head, dimensionality reduction and mean fit inside each leave-one-out fold |
| Baselines | Surface literal (TF-IDF), a general text encoder (BGE-large) on the same text, and a shuffled-label control |
| Certification | At the located sites the canonical frame fits at 100% energy and passes byte-equal replay; a doctored bin is rejected |
The model is public. The probe reads it; it does not change it.
Open on Hugging Face