What Spatial Memory Must Store: Occlusion as the Test for Language-Agent Memory
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Abstract (arXiv)
Language-agent "memory palace" systems anchor each memory to a world coordinate, on the intuition that geometry adds something text cannot. We make that intuition testable and report three results. First, the memory-palace default of folding spatial proximity into a linear blend beside recency and importance does not help and can hurt: in a pre-registered recall experiment the shipped blend fails its own frozen test (mean Delta-Hit@5 -0.0375, Wilcoxon p=0.306), sitting at a position-blind baseline, while a geometry-led weighting wins decisively (+0.3208, p<10^-15): geometry must lead recall when the query regime is spatial. Second, memory recall and visibility must be separated: recall is occlusion-blind by design (you correctly remember the next room behind a wall), while visibility is a perception predicate over stored geometry that the live system never computed. A one-line ray-versus-voxel digital differential analyzer (DDA), re-pointed from the gaze ray the agent already casts, supplies it: text and the live FoV cone both score 0.000 on 849 behind-wall targets while cone-plus-DDA reaches 0.982 (exact McNemar p<10^-6); coordinate recall separately resolves near-duplicate locations a cosine null cannot (1.000 vs 0.533, n=150). Third, the visibility predicate is confirmed live under a git-committed pre-registration (SPMEM-OCC-LIVE-v1: eight scripted worlds, automated oracle scoring, 96 behind-wall targets, false-visible 1.000->0.000, pooled exact McNemar p=2.5x10^-29), a run that surfaced and fixed a real relay anchor defect. We concede that occlusion-needs-geometry is near-tautological; the contribution is the measurement and isolation, separating what spatial memory must store from how it is read. These pilots power a frozen confirmatory study (SPMEM-ZERO-REAL-PREREG-v1); the full human-authored multi-world study with blind raters remains future work.
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References · 13
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
- 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,453
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- 2025A-MEM: Agentic Memory for LLM Agentscited by 1,063
- 2025Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memorycited by 779
- 2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrievalcited by 532
- 2025Zep: A Temporal Knowledge Graph Architecture for Agent Memorycited by 400
- 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 281
- 20243D-Mem: 3D Scene Memory for Embodied Exploration and Reasoningcited by 75
- 2024Project Sid: Many-agent simulations toward AI civilizationcited by 49
- 2025Vision to Geometry: 3D Spatial Memory for Sequential Embodied MLLM Reasoning and Explorationcited by 5
- 2026GSMem: 3D Gaussian Splatting as Persistent Spatial Memory for Zero-Shot Embodied Exploration and Reasoningcited by 5
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- 2026RenderMem: Rendering as Spatial Memory Retrievalcited by 1
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