# type: lib :: Lib
The results proved that actively self-evolving memory vastly outperforms a static skill library. On the highly diverse GAIA benchmark, Memento-Skills improved test set accuracy by 13.7 percentage points over the static baseline, achieving 66.0% compared to 52.3%. On the HLE benchmark, where the domain structure allowed for massive cross-task skill reuse, the system more than doubled the baseline's performance, jumping from 17.9% to 38.7%.
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