metrics

Exp 0 - metrics report

Layer 1 · PCFG toy 4L d_model=448 / pcfg · matryoshka_hook_resid_post_L1 · 1,792 latents in 8 blocks · 1,016,600 tokens over 3400 docs · edge: reverse coverage ≥ 0.5, both endpoints fire ≥ 20

Block pair 0->1 - 327 candidate edges

parent -> child R F PMI recon P/C gain recon? surv sib parent label child label
18 -> 326 0.99 0.34 1.37 0.58/0.08 Y 1.00 0.03 feature 18 feature 326
109 -> 247 0.86 0.01 1.22 1.55/0.04 Y 1.03 - feature 109 feature 247
31 -> 247 0.85 0.01 1.16 0.57/0.04 Y 1.03 - feature 31 feature 247
34 -> 247 0.84 0.01 1.19 1.91/0.04 Y 1.02 - feature 34 feature 247
98 -> 247 0.84 0.01 1.18 1.60/0.04 Y 1.02 - feature 98 feature 247
142 -> 247 0.84 0.01 1.21 0.60/0.04 Y 1.02 - feature 142 feature 247
201 -> 247 0.84 0.01 1.15 1.52/0.04 Y 1.02 - feature 201 feature 247
120 -> 247 0.83 0.01 1.23 0.22/0.04 Y 1.02 - feature 120 feature 247

Block pair 1->2 - 1 candidate edges

parent -> child R F PMI recon P/C gain recon? surv sib parent label child label
232 -> 669 0.56 0.04 2.45 0.09/0.33 Y 1.01 - feature 232 feature 669

Block pair 2->3 - 2 candidate edges

parent -> child R F PMI recon P/C gain recon? surv sib parent label child label
541 -> 675 0.75 0.05 3.26 0.08/0.19 Y 1.00 - feature 541 feature 675
568 -> 675 0.67 0.05 3.36 0.04/0.19 Y 0.94 - feature 568 feature 675

Block pair 3->4 - 0 candidate edges

Block pair 4->5 - 1 candidate edges

parent -> child R F PMI recon P/C gain recon? surv sib parent label child label
965 -> 1172 0.98 0.05 3.94 0.27/0.40 Y 1.00 - feature 965 feature 1172

Block pair 5->6 - 0 candidate edges

Block pair 6->7 - 1 candidate edges

parent -> child R F PMI recon P/C gain recon? surv sib parent label child label
1506 -> 1634 0.56 0.08 3.75 0.12/0.17 Y 0.84 - feature 1506 feature 1634