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Kitaev and colleagues: Reformer memory-efficient sequence modeling

Combined locality-sensitive hashing attention, reversible layers and chunked feed-forward computation to reduce long-sequence training costs.

What is recorded here?

Combined locality-sensitive hashing attention, reversible layers and chunked feed-forward computation to reduce long-sequence training costs.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

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.

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People and systems

Nikita Kitaev; Łukasz Kaiser; Anselm Levskaya

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

Kitaev and colleagues: Reformer memory-efficient sequence modeling

Combined locality-sensitive hashing attention, reversible layers and chunked feed-forward computation to reduce long-sequence training costs.

Scientific scope

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.

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

Nikita Kitaev; Łukasz Kaiser; Anselm Levskaya

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.

Original sources