SuperLocalMemory V3.3 implements a cognitive memory taxonomy with mathematical forgetting and multi-channel retrieval, reaching 70.4% on LoCoMo in zero-LLM mode.
Natural gradient works efficiently in learning.Neural Computation, 10(2): 251–276, 1998
2 Pith papers cite this work. Polarity classification is still indexing.
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Introduces Relative Geometric Conflict (RGC) using gradient direction comparison and empirical Fisher trace factorization to improve reliability estimation beyond loss or confidence signals in noisy-label training.
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SuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems
SuperLocalMemory V3.3 implements a cognitive memory taxonomy with mathematical forgetting and multi-channel retrieval, reaching 70.4% on LoCoMo in zero-LLM mode.
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Radial-Angular Geometry for Reliable Update Diagnosis in Noisy-Label Learning
Introduces Relative Geometric Conflict (RGC) using gradient direction comparison and empirical Fisher trace factorization to improve reliability estimation beyond loss or confidence signals in noisy-label training.