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UC Santa Barbara's TTME memory method outperforms test-time training on math tasks

1 article1 sourcesince Oct 29Last article 1h ago · Oct 29, 1:15 AM ET

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UC Santa Barbara researchers introduce TTME, a method that keeps model weights fixed and stores lessons from earlier attempts in memory.

Across 5 math tasks, 2 frameworks, and 3 models, TTME beat the reported test-time training scores every time, according to the researchers' paper as reported by Rohan Paul on X.

With Qwen3-8B on 3 tasks, TTME used 82.8% to 84.6% fewer FLOPs and 47.7% to 58.4% less runtime than test-time training.

Written by AI from the articles below · updated Oct 29, 1:32 AM ET

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Latest developmentOct 29, 1:15 AM ET

UC Santa Barbara's TTME beats test-time training on math discovery with less compute

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Oct 29

1:15 AM
Rohan Paul@rohanpaul_aiX
UC Santa Barbara's TTME beats test-time training on math discovery with less compute
AIUC Santa Barbara researchers present TTME, which keeps model weights fixed and stores lessons from earlier attempts in memory. Across 5 math tasks, 2 frameworks, and 3 models, TTME beat the reported test-time training scores in every case. With Qwen3-8B on 3 tasks, it used 82.8% to 84.6% fewer FLOPs and 47.7% to 58.4% less runtime.

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