Podracing III: Cubric Lite — 0.9362 BPB

[newjordan]

Summary

• 3-seed mean val_bpb = 0.9362 (seeds 2045=0.9357, 43=0.9362, 300=0.9365)
• 11L/512d U-Net with legal score-first 7-gram backoff (orders 2-7) + entropy-adaptive alpha + per-order adaptive alpha scaling (Cubric Lite)
• 0.026 BPB improvement over Podracing II (Podracing II: Electric Bugaloo — 0.9625 BPB (3-seed mean, all sub-0.964) #753, 0.9625 mean)
• Artifact: 15.59 MB (int6+zstd), under 16 MB budget
• Original contribution: per-order adaptive alpha scaling

What Changed vs Podracing II (#753)

One eval-time addition, no training changes:

Per-order adaptive alpha scaling ("Cubric Lite"): During n-gram eval, track how often each order's n-gram probability beats the model's probability on already-scored tokens. Every 32 batches, adjust per-order alpha multipliers. Converged multipliers: **UNDEREXPLORED

o2:0.300  o3:0.300  o4:0.970  o5:2.000  o6:2.000  o7:2.000

Key finding: 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 gain.

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) using training data only
• Cubric adaptation runs during eval using only already-scored token statistics

Credits

• N-gram eval cache concept: @deanbrr (PR Record: 5-gram Eval Cache + LeakyReLU² + Parallel Muon val_bpb: 1.0920 (3-seed mean, std 0.0007) | ~15.9 MB | 8×H100 SXM #659)
• Multi-order backoff + adaptive alpha: @Asukabot0 (PR Record: First Legal Sub-1.0 BPB — Multi-order N-gram Backoff + Entropy-Adaptive Alpha (val_bpb=0.9674, 3-seed) #727)
• Per-order adaptive alpha scaling (Cubric Lite): @newjordan (original)
• Base architecture: @signalrush (PR Record: 11L EMA + GPTQ-lite + warmdown3500 + [email protected] (val_bpb=1.1233) #414)

Test plan

• 3-seed verification (2045, 43, 300)
• All seeds under 16 MB
• GPTQ uses training data only
• N-gram eval is score-first
• Cubric uses only already-scored data
• Training logs included for all seeds

🤖 Generated with Claude Code

[MatoTeziTanka]

Community Review — Podracing III: Cubric Lite — 0.9362 BPB

BPB: 0.9362 | Compliance: FLAG — hashed n-gram cache with target-in-key (PR #779 family pattern)

What I found in the code (head SHA 67b952d7c73b, file records/track_10min_16mb/2026-03-25_PodracerIII_cubric_lite_8xH100/train_gpt.py):

The n-gram lookup key at line 1101 is constructed by XOR-ing the target token into the hash:

line 1101: full_key = ((ctx_hash ^ (tgt_np[v_idx] * primes[ctx_width % len(primes)])) & mask).astype(np.int64)

The code default is NGRAM_EVAL_ORDER=0 (off), but the actual submission logs show ngram_eval:order=7 — the n-gram cache was active during the scored eval run. The 0.9362 BPB is produced with the n-gram cache enabled, not by the neural model alone.

This matches the full_key = ((ctx_hash ^ (target * primes[k])) & mask) construction that @valerio-oai ruled disallowed on PR #779 (comment 4145781641, 2026-03-27). Per the mechanism explanation, hashing the target token into the lookup key only reweights the correct token — in the hash-collision limit this drives P(correct) → 1 regardless of the data, which inflates the reported BPB without producing real compression.

Per Issue #1017 condition 1, p_t may depend only on the artifact and x_1...x_{t-1}. Because the lookup key at line 1101 is a function of the target token, the count read at scoring position t depends on x_t itself — which is the core violation the #779 ruling targets.

Cluster context: this same structural pattern has been closed on 15+ PRs under the #779 ruling as of 2026-04-11 (#779 itself, #770, #798, #808, #825, #786, #797, #909, #940, #761, #776, #788, #774, #778, #715, #758, #702 upstream).

CPU smoke test (CT2038 proteus-engine, 2026-04-11): import OK in 0.05s, dim=512, layers=11, vocab=1024, code=98717 B, SMOKE_TEST_PASS

Verdict: COMPLIANCE FLAG — target-in-key hashed n-gram cache, same family as PR #779. N-gram cache confirmed active in submission logs (order=7).

Recommendation to @cocohearts @valerio-oai @0hq @yuzhougu-oai @notapplica: CLOSE under the same ruling as the rest of the family-bug cluster. A context-only resubmission (drop the target from the lookup key and use a full-vocabulary reweighting from a single context row, per @valerio-oai's suggested legal path on #779) would be welcomed.

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Reviewed by @MatoTeziTanka — The Agora. CPU smoke test (CT2038 proteus-engine, 2026-04-11): import OK in 0.05s, dim=512, layers=11, vocab=1024, code=98717 B, SMOKE_TEST_PASS. Classification via manual code review + submission log audit (classifier initially mis-tagged as PURE_NEURAL_CLEAN because NGRAM_EVAL_ORDER=0 default hides the active eval path — submission logs confirm order=7 was used). This review was spot-checked before posting — if the template misread your code, please call it out so I can iterate the classifier.