repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
Frappucc1no/recall-loom
Project memory for long-running AI work across agents, models, and sessions. Keep context, decisions, progress, and next steps in local project files.
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 58%MemSyco-Bench: Benchmarking Sycophancy in Agent Memory →
- PossiblePossibly related (embedding) · 56%MRMS: A Multi-Resolution Memory Substrate for Long-Lived AI Agents →
- PossiblePossibly related (embedding) · 55%AgentCore-8B →
- PossiblePossibly related (embedding) · 55%Self-Evolving World Models for LLM Agent Planning →
- PossiblePossibly related (embedding) · 54%I built an open-source memory governance layer for AI assistants - looking for technical feedback [P] →
- PossiblePossibly related (embedding) · 50%Choosing the Right AI Agent Memory Strategy: A Decision-Tree Approach →
- PossiblePossibly related (embedding) · 57%Show HN: ContextVault – Shared memory layer for your AI and your team →
- PossiblePossibly related (embedding) · 50%Fractale-350M-base: memory as trained behaviour instead of long context, a fully open research release →
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newsI built an open-source memory governance layer for AI assistants - looking for technical feedback [P]paperMRMS: A Multi-Resolution Memory Substrate for Long-Lived AI AgentsnewsChoosing the Right AI Agent Memory Strategy: A Decision-Tree ApproachpaperSelf-Evolving World Models for LLM Agent PlanningmodelAgentCore-8BpaperMemSyco-Bench: Benchmarking Sycophancy in Agent MemorynewsShow HN: ContextVault – Shared memory layer for your AI and your teamnewsFractale-350M-base: memory as trained behaviour instead of long context, a fully open research release