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LOCI introduces a hybrid spatial memory architecture for streaming video world models, combining key-value caches with a recurrent linear-attention memory conditioned on camera geometry. It reproduces revisited content more faithfully than full-softmax baselines while reducing peak memory by about 30% and enabling constant-memory streaming of long videos.
HomeBody is a humanoid robot system that explores environments, builds digital twins using Real2Sim, and leverages VLMs to perform autonomous long-horizon tasks like tidying kitchens.
This paper empirically studies how VLM agents with persistent spatial memory fail when memory becomes stale, using a dynamic FrozenLake testbed. It finds that trusting stale memory can more than double death rates, and that read-time auditing helps but does not fully close the gap.
This paper empirically studies spatial memory staleness in vision-language-model agents, finding that models often ignore contradictory visual evidence and that trusting stale memory can increase safety risks. The authors propose auditing mechanisms but show that visual grounding under memory-observation conflicts remains a major open challenge.
This paper investigates whether spatial geometry improves language-agent memory recall, demonstrating that geometry must lead recall over recency and importance, and that a ray-tracing visibility predicate is crucial for occlusion handling in 3D voxel worlds.
This paper reveals that superior spatial memory in food-caching birds arises from a geometric phase transition in hippocampal population activity, from disorganized 'mist' to crystalline collective coding, enabling over 100-fold higher capacity.