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New geometric framework simplifies Structured State Space Models

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced a novel geometric framework for constructing discrete-time Structured State Space Models (SSMs), which are foundational to architectures like Mamba. This new approach utilizes a lag operator to derive the discrete-time recurrence directly, offering a more intuitive and modular design. The framework allows for the creation of new SSMs by combining different basis functions and time-warping schemes, with a specific instance shown to precisely replicate the HiPPO model's recurrence. AI

IMPACT Provides new theoretical tools for designing more flexible and robust sequence models, potentially influencing future architectures.

RANK_REASON The cluster contains an academic paper detailing a new theoretical framework for sequence modeling. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New geometric framework simplifies Structured State Space Models

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The cluster contains an academic paper detailing a new theoretical framework for sequence modeling. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Sutashu Tomonaga, Kenji Doya, Noboru Murata ·

    Lag Operator SSMs: A Geometric Framework for Structured State Space Modeling

    arXiv:2512.18965v2 Announce Type: replace Abstract: Structured State Space Models (SSMs), which are at the heart of the recently popular Mamba architecture, are powerful tools for sequence modeling. However, their theoretical foundation relies on a complex, multistage process of …

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