Verified claim · AI-ML · 100% confidence
Mamba-2 introduced in: Dao & Gu 2024 — structured state space duality.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 07abb25f8fc2c1d6
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Structured fields
- Subject
- Mamba-2
- Predicate
introduced_in- Object
- Dao & Gu 2024 — structured state space duality
- Confidence
- 100%
- Tags
- mamba-2 · state-space-model · ssm · princeton · cmu · 2024 · introduced_in
Sources (2)
[1] preprint · arXiv (Dao, Gu / Princeton + Carnegie Mellon) · 2024-05-31
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality“We propose a framework of structured state-space duality (SSD) that connects SSMs and variants of attention through various decompositions of a well-studied class of structured semi-separable matrices. We then design a new architecture, Mamba-2, whose core layer is a refinement of Mamba's selective SSM that is 2-8X faster.”
[2] github release · state-spaces / Princeton + CMU · 2024-05-31
Mamba + Mamba-2 official GitHub repository
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Evidence comes from 2 primary sources: arXiv (Dao, Gu / Princeton + Carnegie Mellon), state-spaces / Princeton + CMU. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/07abb25f8fc2c1d6.json includes an HMAC-SHA256 signature for audit verification.
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// "Mamba-2 introduced in: Dao & Gu 2024 — structured state space duality."Python
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# "Mamba-2 introduced in: Dao & Gu 2024 — structured state space duality."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_mamba_2_fact() -> dict:
"""Fetch the verified SourceScore claim for Mamba-2."""
r = httpx.get("https://sourcescore.org/api/v1/claims/07abb25f8fc2c1d6.json")
return r.json()