Memory Has Geometry (arXiv:2609.17969v1): non‑uniform geometric memory for long‑horizon personalization
New arXiv preprint argues that long-term personalization should represent memory as a user-specific dynamical state space with locally heterogeneous geometry rather than as static records in a single latent space. The paper proposes trajectory-conditioned reconstruction (not just nearest-neighbor lookup) to capture stable vs. volatile regions, variable-rate drift, heterogeneous neighborhoods, and uncertainty about current user state.