Method evidence record
Mamba (State Space Model)
Mamba is a sequence model architecture introduced by Gu and Dao in 2023 that achieves linear-time complexity while maintaining strong performance on language modeling tasks. By combining state space models with input-dependent selectivity, Mamba addresses the quadratic complexity of transformers while preserving modeling power.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Taxonomic method record · ml-model / deep-learning
Open full method Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
No curated claims yet
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.