ambiguous · filed under model architecture
Natively trained sparsity
The evidence provides only this broad description and does not identify a more specific method.
- source
- 1
- model
- 1
- lab adopt it
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- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
Most likely natively trained sparsity.
usedtraining objectivein MiniMax-M3MiniMax
Filed alongside
Other methods under model architecture :: token mixer :: sparse attention.
DeepSeek Sparse AttentionCompressed Sparse AttentionQwen Sparse AttentionSparse attentionHeavily Compressed AttentionGated DeepSeek Sparse AttentionCSA2 Full ModeKV-outer sparse attentionProgressive sequence-length extension for sparse attentionSparse-attention continued pre-training with joint model and indexer optimizationCross-layer KV and index reuse with statically assigned CSA2 modesFixed-budget sparse-attention selectionFrom-scratch sparse attention training without dense warmupJoint backbone and indexer training under sparse attentionNative Sparse AttentionNoPE sparse multi-head latent attentionQSA micro-block compression at ratio 4Sequential block processingSparse retrieval over long contextsSparse softmax attentionToken-wise compressionTwo-stage introduction of sparse attentionTwo-stage sparse attention