Podracing III: Cubric Lite — 0.9362 mean BPB (3-seed)

Per-order adaptive alpha scaling on legal score-first 7-gram backoff.
Tracks per-order beat rate on already-scored tokens, suppresses noisy
low orders (2-3 → 0.3x alpha), boosts accurate high orders (5-7 → 2.0x).

Results (seeds 2045/43/300):
  Sliding BPB (no n-gram): 1.1198 mean
  Cubric n-gram BPB: 0.9362 mean (0.9357/0.9362/0.9365)
  Artifact: 15.59 MB (int6+zstd)

0.026 BPB improvement over Podracing II (openai#753, 0.9625).
Original contribution: per-order adaptive alpha scaling.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: Octavian

records/track_10min_16mb/2026-03-25_PodracerIII_cubric_lite_8xH100/README.md

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+# Podracing III: Cubric Lite
+
+## Results
+
+| Seed | Sliding BPB | Cubric N-gram BPB | Artifact |
+|------|-------------|-------------------|----------|
+| 2045 | 1.1193 | **0.9357** | 15.59 MB |
+| 43 | 1.1200 | **0.9362** | 15.58 MB |
+| 300 | 1.1202 | **0.9365** | 15.58 MB |
+| **Mean** | **1.1198** | **0.9362** | — |
+
+## What Changed vs Podracing II (#753)
+
+One eval-time improvement, no training changes:
+
+1. **Per-order adaptive alpha scaling ("Cubric Lite")**: Track how often each n-gram order's probability beats the model's probability on already-scored tokens. Every 32 batches, adjust per-order alpha multipliers. Orders that consistently beat the model get boosted (up to 2.0x), orders that consistently lose get suppressed (down to 0.3x).
+
+**Learned multipliers (converged by step 48):**
+```
+o2:0.300  o3:0.300  o4:0.970  o5:2.000  o6:2.000  o7:2.000
+```
+
+Key insight: bigrams and trigrams (orders 2-3) were actively harming BPB by injecting noisy predictions at the same alpha as high-order matches. Suppressing them to 30% of base alpha and boosting orders 5-7 to 200% = 0.026 BPB improvement over Podracing II (0.9625 → 0.9362).
+
+## Compliance
+
+- Score-first, backward-looking: n-gram cache built from already-scored tokens only
+- Alpha depends solely on model's own softmax entropy — no target/label access
+- Per-order multipliers use beat-rate statistics from already-scored tokens — same legality as the score-first table update
+- No oracle selection, no min-NLL comparison
+- GPTQ calibration runs inside training phase (before wallclock stop)
+- Cubric multiplier adaptation runs during eval, uses no training data
+
+## Credits
+
+- N-gram eval cache concept: @deanbrr (PR #659)
+- Multi-order backoff + adaptive alpha inspiration: @Asukabot0 (PR #727)
+- Per-order adaptive alpha scaling (Cubric Lite): @newjordan (original contribution)
+- Base architecture: @signalrush (PR #414)
+
+## Reproduce
+
+```bash
+SEED=2045 bash concepts/podracer/podracer_green/run.sh
+```
+
+8xH100 SXM, 600s training + ~120s eval.

records/track_10min_16mb/2026-03-25_PodracerIII_cubric_lite_8xH100/submission.json

@@ -0,0 +1,11 @@
+{
+  "author": "Frosty40",
+  "github_id": "newjordan",
+  "name": "Podracing III: Cubric Lite — Per-Order Adaptive Alpha",
+  "blurb": "11L/512d U-Net with legal score-first 7-gram backoff (orders 2-7) + entropy-adaptive alpha + per-order adaptive alpha scaling (Cubric Lite). Orders 2-3 suppressed (0.3x), orders 5-7 boosted (2.0x). 3-seed mean val_bpb=0.9362. N-gram concept credited to @deanbrr (PR #659).",
+  "date": "2026-03-25T23:30:00Z",
+  "val_loss": 1.5807,
+  "val_bpb": 0.9362,
+  "bytes_total": 15588220,
+  "bytes_code": 100286
+}