Every run is saved with its full inputs &
hyper-parameters. Load a prior session to reproduce it or tweak its
edits and re-run.
capture → AV(h) → edit verbalization → Δ = AR(edit) − AR(AV(h)) → α-sweep.
Results saved on the Ubuntu box under experiments/ui/runs/.
1 Prompt & decode
Type the prompt the model receives, then run. Greedy is
executed 3× to prove the capture is deterministic.
2 Decode result
greedy ×3 (must be identical → deterministic capture)
sampled previews (T=1.0, top-p=0.95)
3 Pick a START position for the AV(h) scan
positions < 50 decode to noise (dimmed).
Click a token to set where the scan begins; all positions from there to
the end get verbalized.
start = —
pos
token
AV(h) explanation — click a row to steer that position
4 Multi-token steering
(0 selected)
Click AV rows in step 3 to add/remove them from the edit
set. Edit each token's verbalization below — the diff shows exactly what
you changed vs the original AV. On run, Δp = AR(editedp)
− AR(AV(hp)) is computed per token and all are injected
simultaneously on the prefill pass.