[Non-record] Meta-Learned TTT + Error-Guided Adaptation Analysis (val_bpb=1.1645)#296
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sseanliu wants to merge 2 commits intoopenai:mainfrom
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[Non-record] Meta-Learned TTT + Error-Guided Adaptation Analysis (val_bpb=1.1645)#296sseanliu wants to merge 2 commits intoopenai:mainfrom
sseanliu wants to merge 2 commits intoopenai:mainfrom
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mrdavtan
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Mar 21, 2026
- Add leaderboard table: jfprincz 1.1271 is new target; mohosy racing same stack - Add Reptile meta-TTT finding (PR openai#296): 10x better than naive TTT with SmearGate; error-guided TTT is negative; 13L crossover point identified - Add SWA checkpoint count finding (PR openai#238): 84 checkpoints reverses quant gap; explains why our WD=1200 SWA showed no effect - Update jfprincz entry to include PR openai#287 results (1.1271) - Add meta-lessons 10 and 11
Combines PR openai#287 (XSA + EMA + Int6 QAT) with PR openai#254 TTT adaptation. Changes: FA2 fallback import, TTT hyperparameters, ttt_adapt function, TTT call before torch.compile in eval section.
This was referenced Mar 21, 2026
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Summary
Non-record research submission exploring test-time adaptation strategies for compressed language models at 16MB scale.
Key findings
Score
See README for full methodology and analysis.