A brain-inspired navigation system stores landmarks, routes, and map-like voxel features in structured spatial memory and uses MLLM-powered retrieval to achieve strong results across object, instance, instruction, and question-answering navigation.
Overlapping community detection algorithms using Modularity and the cosine
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The issue of network community detection has been extensively studied across many fields. Most community detection methods assume that nodes belong to only one community. However, in many cases, nodes can belong to multiple communities simultaneously.This paper presents two overlapping network community detection algorithms that build on the two-step approach, using the extended modularity and cosine function. The applicability of our algorithms extends to both undirected and directed graph structures. To demonstrate the feasibility and effectiveness of these algorithms, we conducted experiments using real data.
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From reactive to cognitive: brain-inspired spatial intelligence for embodied agents
A brain-inspired navigation system stores landmarks, routes, and map-like voxel features in structured spatial memory and uses MLLM-powered retrieval to achieve strong results across object, instance, instruction, and question-answering navigation.