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The author details their journey from a flat vector store to a graph database (FalkorDB) for AI memory, enabling multi-hop reasoning, temporal queries, and provenance tracking in their LocalClaw project.
This paper presents a hybrid neural-symbolic pipeline for extracting follow-up instructions from clinical notes, using BioBERT and deterministic date arithmetic. It achieves high performance (Pair F1 ~0.99) compared to generative baselines.
Graphiti is an open-source tool that builds human-like memory for AI agents using a continuously evolving, temporally-aware knowledge graph, achieving up to 18.5% higher accuracy and 90% lower latency compared to MemGPT.
RAGA is an LLM-driven autonomous agent that constructs knowledge graphs via a read-search-verify-construct cognitive loop and integrates hybrid symbolic-vector retrieval for retrieval-augmented generation, with experimental gains on scientific QA datasets.