Radar ·
Latent Sparse Attention: open research release on subquadratic attention
Radar notes the open research release of Latent Sparse Attention (LSA). The author claims accuracy matching full attention on ultra-long contexts, with speedups up to 22.7x for sparse attention and 72.4x for full attention, and shows where sparse attention time is spent at 10 million tokens.
Radar notes the open research release of Latent Sparse Attention (LSA), dated 2 November 2026 according to the source. The author claims the method matches full attention accuracy on ultra-long contexts, with speedups of up to 22.7x for sparse attention and up to 72.4x for full attention. According to the description, the work shows where sparse attention time is spent with 10 million tokens and reports speed gains on long context. The source is a short briefing and gives no further details on methodology, benchmarks, models tested or reproduction conditions.
To verify, consult the original release named in the Radar source, read the methodology, benchmarks and experimental conditions before citing the numbers, and confirm that the comparisons use the same baseline. Rota Nacional does not implement or guarantee LSA, and this content does not describe a platform capability. Because the topic has no direct privacy angle, the relevant point is protecting the organization's data if someone uses AI to study or apply the material: do not paste internal documents, personal data or credentials into prompts.
Original source: Latent Sparse Attention: release de pesquisa sobre atenção subquadrática