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        "url": "https://arxiv.org/abs/2405.21060",
        "title": "Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality",
        "publisher": "arXiv (Dao, Gu / Princeton + Carnegie Mellon)",
        "publishedDate": "2024-05-31",
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        "excerpt": "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."
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        "url": "https://github.com/state-spaces/mamba",
        "title": "Mamba + Mamba-2 official GitHub repository",
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