What is recorded here?
Added a low-cost lightning indexer with top-k latent KV selection and staged dense-to-sparse continued training, alongside scalable reasoning/tool-use training and synthetic interactive tasks.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
MLA/MQA and prior RL are inherited. Sparse main attention does not eliminate the indexer's pairwise scoring cost or guarantee equivalence to dense attention. September experimental and December full releases share DSA; Speciale benchmark claims are not official competition participation.
Read the original work
- DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
- DeepSeek-AI: lightning-indexed sparse attention and agentic training — author/institution implementation
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
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. The recorded author list is incomplete.
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English catalogue narrative
DeepSeek-AI: lightning-indexed sparse attention and agentic training
Added a low-cost lightning indexer with top-k latent KV selection and staged dense-to-sparse continued training, alongside scalable reasoning/tool-use training and synthetic interactive tasks.
Scientific scope
MLA/MQA and prior RL are inherited. Sparse main attention does not eliminate the indexer's pairwise scoring cost or guarantee equivalence to dense attention. September experimental and December full releases share DSA; Speciale benchmark claims are not official competition participation.
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
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.