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Skills2026-03-18 · source-backed
Three-phase lifecycle: Phase 1 converts dialogue into MemCells (episodic traces + atomic facts + foresight signals); Phase 2 organizes into MemScenes with conflict resolution; Phase 3 performs MemScene-guided retrieval for minimal sufficient context. State-of-the-art on LoCoMo and LongMemEval benchmarks. arXiv
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July 17, Product Hunt's #1 product was Unabyss for Claude: shared memory across all apps and LLMs, 598 votes. July 18, #1 was ZooData: "the data layer for AI agents," 606 votes. Neither is an application. Both are substrate. (Product Hunt) One launch is noise. Two consecutive...
arXiv 2608.12990 from Dongfang Li, Baotian Hu, Min Zhang and colleagues replaces turn-level memory consolidation with semantic boundary detection, reporting 89.22% on LoCoMo and 92.20% on LongMemEval-S while cutting construction tokens 86.0% and 75.9% versus the A-Mem baseline...
MemPalace (57,821 stars, v3.6.0) reports 96.6% raw recall@5 on LongMemEval with no LLM required, 98.4% with hybrid v4 on a held-out 450 questions, LoCoMo R@10 rising 60.3% → 88.9%, ConvoMem 92.9%, MemBench 80.3%, while explicitly refusing head-to-head comparison against Mem0,...
MIT-licensed Rust, created August 27. It stores LLM observations as provenance-tracked facts with stratified rules and incremental derivation, exposed to a harness over MCP, so the model does language extraction while the database keeps logical consistency. Reported: 0.463 ±0....
Compounding at ~847 stars/day to 97,447, built on tree-sitter AST parsing across 36+ languages plus Leiden community detection, with no vector store anywhere in the pipeline. Every edge is labeled EXTRACTED (explicit in source) or INFERRED (derived through resolution), which i...
Four parallel retrieval strategies (semantic, temporal, entity, opinion) merged through cross-encoder reranking with atomic fact extraction on every write. Ships an MCP server for Claude Code adoption via single JSON config. Source
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