memory: snapshot — semif live + averaging spike (build 0.1.3 + fast-kernel trial next), restic creds out of units on all 8 hosts, infra-ops on vm-esh-nas, augaman fv-ml1 instance removed; 4 foot-guns
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# `[2026-09-27]` SemIf order-averaging: spiked, Prime ruled build + fast-kernel trial
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**Finding (Prime's probes):** SemIf's single-ordering answer leans toward whichever option is listed
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first on ambiguous inputs. For "It's 2AM and I'm bored", the top pick flipped from casual 0.685 to booty
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call 0.760 when the order was reversed.
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**Spike** (`739aa03`, `services/semif-serve/spike/`, no service change). SemIf authored144 +
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perturbations108, 252 rows in 72 groups, 3 options each, with all 6 orderings of every row sent in one
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shared request:
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| method | accuracy |
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|---|---|
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| single ordering, as sent | 78.6% |
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| expected single ordering | 80.0% |
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| 3 rotations, log-mean | **87.7%** (+9.1 pts, group-bootstrap 95% CI +4.7..+13.8) |
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| all 6 orderings, log-mean | 88.1% |
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Rows where the rotations agree unanimously: 161 rows, 94.4% accurate. Split rows: 91 rows, 75.8%.
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The service is deterministic, so the CI measures item sampling, not run noise. This is one task family
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(evidence interpretation, 3 options), not our workload.
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**Latency** (`spike/latency-2026-09-27.txt`, from nh3-dev, network floor 31 ms):
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- `/decide` short: 71 ms end to end (38 ms server);
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- 3 rotations shared: 113 ms (79 ms);
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- 6 orderings: 137 ms (99 ms);
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- a ~2k-token state: 210 ms (169 ms).
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**Prime ruled (2026-09-27 ~0250): build it in, and try the fast kernels too.**
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- Averaging design: opt-in `orderings: rotations|all` (all only ≤ 4 options); all orderings in one shared
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batch; per-ordering SemIf results returned unchanged; a `combined` block (log-mean, top, agreement,
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spread); orderings count toward `max_decisions`.
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- Fast kernels: `causal_conv1d` + `flash-linear-attention` are missing, so transformers runs Qwen3.5's
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reference PyTorch paths. Adopt them only if the authored144 parity re-check holds.
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Tracked in the in-flight SemIf section. See [[2026-09-27-semif-live-on-fv-ml1-gpu1]].
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