What is recorded here?
Used dilated attention with exponentially growing receptive fields and sequence-partitioned execution to reduce long-sequence attention computation and communication.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Billion-token evidence is distributed forward-runtime feasibility, not a trained model demonstrating billion-token reasoning or end-to-end learning quality. Sparse attention is not exact dense attention; scaling depends on the stated device/data layout.
Read the original work
- LongNet: Scaling Transformers to 1,000,000,000 Tokens
- Ding et al.: LongNet dilated distributed attention — official project source
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Jiayu Ding; Shuming Ma; Li Dong; Xingxing Zhang; Shaohan Huang; Wenhui Wang; Furu Wei
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
Ding et al.: LongNet dilated distributed attention
Used dilated attention with exponentially growing receptive fields and sequence-partitioned execution to reduce long-sequence attention computation and communication.
Scientific scope
Billion-token evidence is distributed forward-runtime feasibility, not a trained model demonstrating billion-token reasoning or end-to-end learning quality. Sparse attention is not exact dense attention; scaling depends on the stated device/data layout.
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
Jiayu Ding; Shuming Ma; Li Dong; Xingxing Zhang; Shaohan Huang; Wenhui Wang; Furu Wei
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.