PW
A mechanism for maintaining recent information in a recurrent state. It separately stores pure write content within a sliding window as a high-precision vector, and merges that content into the low-bit historical state once it leaves the window.
Timeline (last 90 days)
The study proposes two methods, global gradient-aware allocation (GGA) and pure-write sliding window (PW), to simultaneously address the challenges of precision allocation and recent-information maintenance within a storage budget.
PW independently maintains the pure-write content of the most recent period, stores it as FP8 vector pairs that fully participate in the GDN state transition, and merges it into the low-bit historical state only after it leaves the sliding window.
GGA handles precision allocation along the spatial dimension, while PW handles information freshness along the temporal dimension; the two are complementary, forming a combined strategy of allocation by sensitivity and layering by time.
All Facts (3)
The study proposes two methods, global gradient-aware allocation (GGA) and pure-write sliding window (PW), to simultaneously address the challenges of precision allocation and recent-information maintenance within a storage budget.
50%UnverifiedPW independently maintains the pure-write content of the most recent period, stores it as FP8 vector pairs that fully participate in the GDN state transition, and merges it into the low-bit historical state only after it leaves the sliding window.
50%UnverifiedGGA handles precision allocation along the spatial dimension, while PW handles information freshness along the temporal dimension; the two are complementary, forming a combined strategy of allocation by sensitivity and layering by time.
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