Harmonic: Hierarchical State Space Models — an O(L) recurrence that gets better as context grows. Dual-licensed (PolyForm Noncommercial + commercial).
GLACIER: Mamba with infinite memory. This project integrates the Mamba SSM with ICE-Lite, a virtual memory engine, to solve context rot. By adding persistent, time-aware memory, GLACIER gives Mamba the long-term recall of a Transformer while retaining its $O(N)$ speed. Apache 2.0 licensed, by Dopove.
TESM (Token-Entangled State Machine) - A novel LLM architecture based on state entanglement theory, combining State Space Models with local entanglement mechanisms for efficient long-sequence modeling
CRSD is a minimal, research-oriented sequence modeling framework built from scratch to explore state-space models (SSMs) and sequence-to-sequence architectures in PyTorch. It’s designed to be fully reproducible, interpretable, and extensible — suitable both for learning and for building experimental variants such as nonlinear-SSMs, gated decoders
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