Discovered candidate operators — cross-model profiles
Arch-generic dossiers of the UNNAMED load-bearing candidates the discovery sweep surfaced in the RoPE models (which operator_dossier.py, GPT-2-only, could not reach). Each: which content pattern it reads, its causal ΔNLL (mean-ablation), and the channel decomposition (what addresses its key vs what it moves). Two independent harnesses agree where the discovery ind ΔNLL (multi-seed sweep) and the profiled causal ind ΔNLL (this run, fresh probes) line up. Provisional.
23 candidates profiled across 3 models. Sorted by profiled induction ΔNLL.
gemma-2-2b
| head | reads | discovery ind ΔNLL | profiled causal ΔNLL (ind / gen) | KEY top writer (collapse) | VALUE top mover (ΔV-out) |
|---|---|---|---|---|---|
13.7 |
induction | +0.80 | +0.68 / +0.01 | 6.0 (+5%) | 8.0 (0.38) |
0.7 |
induction | +0.45 | +0.34 / +0.06 | — (layer 0) | — |
10.6 |
duplicate | +0.37 | +0.31 / +0.05 | 9.2 (+6%) | 8.0 (0.28) |
5.6 |
induction | +0.43 | +0.25 / +0.01 | 1.4 (+1%) | 4.4 (0.14) |
9.6 |
duplicate | +0.12 | +0.24 / +0.05 | 8.3 (+10%) | 8.0 (0.31) |
0.6 |
duplicate | +0.23 | -0.12 / +0.00 | — (layer 0) | — |
Llama-3.2-1B
| head | reads | discovery ind ΔNLL | profiled causal ΔNLL (ind / gen) | KEY top writer (collapse) | VALUE top mover (ΔV-out) |
|---|---|---|---|---|---|
0.31 |
induction | +7.26 | +7.99 / +0.78 | — (layer 0) | — |
1.31 |
induction | +5.93 | +5.97 / +2.35 | 0.30 (+6%) | 0.29 (0.52) |
1.29 |
induction | +5.57 | +5.56 / +1.96 | 0.30 (+3%) | 0.29 (0.52) |
0.29 |
induction | +2.79 | +2.87 / +0.15 | — (layer 0) | — |
0.13 |
duplicate | +1.64 | +1.70 / +0.15 | — (layer 0) | — |
0.14 |
duplicate | +1.07 | +1.14 / +0.03 | — (layer 0) | — |
0.28 |
induction | +1.25 | +1.07 / +0.05 | — (layer 0) | — |
0.19 |
induction | +0.55 | +0.94 / +0.06 | — (layer 0) | — |
0.18 |
duplicate | +0.45 | +0.63 / +0.18 | — (layer 0) | — |
0.25 |
duplicate | +0.26 | +0.49 / +0.00 | — (layer 0) | — |
0.16 |
duplicate | +0.22 | +0.45 / +0.01 | — (layer 0) | — |
0.22 |
duplicate | +0.23 | +0.37 / +0.00 | — (layer 0) | — |
1.28 |
duplicate | +0.30 | +0.33 / +0.06 | 0.30 (+4%) | 0.29 (0.44) |
0.20 |
duplicate | +0.38 | +0.26 / +0.05 | — (layer 0) | — |
0.21 |
induction | +0.21 | +0.19 / +0.00 | — (layer 0) | — |
Qwen2.5-1.5B
| head | reads | discovery ind ΔNLL | profiled causal ΔNLL (ind / gen) | KEY top writer (collapse) | VALUE top mover (ΔV-out) |
|---|---|---|---|---|---|
1.6 |
duplicate | +0.22 | +0.31 / +0.06 | 0.8 (+4%) | 0.10 (0.18) |
1.5 |
induction | +0.11 | +0.07 / +0.06 | 0.10 (+3%) | 0.11 (0.15) |
Data: xmodel_candidates_summary.json. Regenerate (GPU): xmodel_candidate.py; re-render the page (CPU): xmodel_candidate.py --docs-only. The full per-op battery for these is the RoPE-dossier port (future); this is the channel + causal core.