What is recorded here?
Projected sequence-length key and value dimensions into a lower-dimensional representation to reduce attention computation and storage.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Linear sequence-length cost fixes projection rank; approximation is not exact dense softmax attention or a universal constant-rank theorem.
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People and systems
Sinong Wang; Belinda Z. Li; Madian Khabsa; Han Fang; Hao Ma
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.
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English catalogue narrative
Wang and colleagues: Linformer low-rank attention projection
Projected sequence-length key and value dimensions into a lower-dimensional representation to reduce attention computation and storage.
Scientific scope
Linear sequence-length cost fixes projection rank; approximation is not exact dense softmax attention or a universal constant-rank theorem.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Sinong Wang; Belinda Z. Li; Madian Khabsa; Han Fang; Hao Ma
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.