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  3. SuperLocalMemory V3.3: The Living Brain -- Biologically-Insp
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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

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Evidence Receipt

Freshness: 2026-04-07T20:14:43.591956+00:00

Claims: 0

References: 0

Proof: unverified

Freshness: fresh

Source paper: SuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems

PDF: https://arxiv.org/pdf/2604.04514v1

Repository: https://github.com/qualixar/superlocalmemory

Source count: 0

Coverage: 0%

Last proof check: 2026-04-07T20:14:43.591Z

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Paper Mode

SuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems

Overall score: 7/10
Lineage: 0c7a7330ca0a…
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Canonical Paper Receipt

Last verification: 2026-04-07T20:14:43.591Z

Freshness: fresh

Proof: unverified

Repo: unknown

References: 0

Sources: 0

Coverage: 0%

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Starting…

Dimensions overall score 7.0

GitHub Code Pulse

Stars
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C
Last commit
4/11/2026
Forks
9
Open repository

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Keep exploring

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Prior Work
SuperLocalMemory V3: Information-Geometric Foundations for Zero-LLM Enterprise Agent Memory
Score 7.0stable
Prior Work
D-Mem: A Dual-Process Memory System for LLM Agents
Score 7.0stable
Prior Work
Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers
Score 7.0stable
Prior Work
Novel Memory Forgetting Techniques for Autonomous AI Agents: Balancing Relevance and Efficiency
Score 7.0stable
Higher Viability
Graph-Native Cognitive Memory for AI Agents: Formal Belief Revision Semantics for Versioned Memory Architectures
Score 8.0up
Higher Viability
MemMachine: A Ground-Truth-Preserving Memory System for Personalized AI Agents
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