AWhat changed
Combined locality-sensitive hashing attention, reversible layers and chunked feed-forward computation to reduce long-sequence training costs.
Scientific scope
Combined locality-sensitive hashing attention, reversible layers and chunked feed-forward computation to reduce long-sequence training costs. Hashing approximates attention; reversible layers are inherited from earlier work. Reported near-L-log-L attention costs do not guarantee hardware speedup for every sequence length.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Hashing approximates attention; reversible layers are inherited from earlier work. Reported near-L-log-L attention costs do not guarantee hardware speedup for every sequence length.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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