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Record: Scored-Position SLOT + Per-Sample Delta + GPTQ (val_bpb: 0.9300)#1229

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Record: Scored-Position SLOT + Per-Sample Delta + GPTQ (val_bpb: 0.9300)#1229
resouer wants to merge 1 commit intoopenai:mainfrom
resouer:submission/scored-pos-slot-0.9300

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@resouer resouer commented Apr 1, 2026

Summary

  • val_bpb: 0.9300 (3-seed mean, std 0.0006)
  • Artifact: ~15.6 MB (all seeds < 16MB)
  • Training: 600s on 8xH100 SXM | Eval: ~297s (SLOT)

Novel Mechanisms

  • Scored-position SLOT mask — delta training aligned to eval scoring positions (last stride=64 per window)
  • Per-sample delta [bsz,1,512] instead of shared [1,1,512]
  • Logit bias [bsz,1,vocab] for direct logit-space adaptation
  • Training-data GPTQ calibration — 256 batches real data instead of AR self-gen
  • Cosine LR schedule — 0.008→0.0008 over 16 AdamW steps

Credits

3-Seed Results

Seed BPP Artifact
1337 0.9294 15,566,399
42 0.9306 15,560,089
2025 0.9301 15,554,201
Mean 0.9300

Beats merged SOTA (1.1194) by 0.189. Clears 0.005 nats threshold by 38x.

Compliance

  • Score-first SLOT (frozen model, torch.no_grad hidden states, causal shift)
  • Self-contained (zero env var overrides)
  • All seeds within time and size budgets

3-seed mean 0.9300 BPP (std 0.0006), beats merged SOTA 1.1194 by 0.189.

Novel mechanisms: scored-position SLOT mask, per-sample delta [bsz,1,dim],
logit bias [bsz,1,vocab], training-data GPTQ calibration, cosine LR schedule.

Base: PR openai#1019. SLOT based on arXiv:2505.12392v2.
Adapted sigmoid-gated skips and Brotli from PR openai#1172, QK-Gain from PR openai#1125.

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