Research map / Architectures and efficiency / RNNs and normalization
HiPPO Zoo: Explicit Memory Mechanisms for Interpretable State Space Models
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- UnHiPPO: Uncertainty-aware Initialization for State Space Models (ICML 2025 · similarity 0.87)
- Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing (ICLR 2025 · similarity 0.86)
- MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models (NeurIPS 2026 · similarity 0.86)
- Quantifying Memory Utilization with Effective State-Size (ICML 2025 · similarity 0.85)
- HOPE for a Robust Parameterization of Long-memory State Space Models (ICLR 2025 · similarity 0.85)
- FACTS: A Factored State-Space Framework for World Modelling (ICLR 2025 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
