. . . . "PersonalAI: A Systematic Comparison of Knowledge Graph Storage and Retrieval Approaches for Personalized LLM agents" . . . . . . . . . . . . . . . . . . . "This method is a specific graph traversal algorithm, based on A*, designed for the QA pipeline to extract relevant triples from the memory graph. It employs various heuristics (Inner Product, Weighted Shortest Path, Averaged Weighted Shortest Path) to optimize pathfinding, contributing to the synergized reasoning capabilities of the overall framework." . "A* Retrieval Algorithm" . . . "AriGraph" . . . "Inspired by LLM token generation, this retrieval algorithm constructs multiple semantically relevant paths from a starting vertex in the knowledge graph. It is a key component of the QA pipeline, governed by hyperparameters for depth, path count, and intersection rules, and contributes to the synergized reasoning process by finding optimal information retrieval paths." . "BeamSearch Retrieval Algorithm" . . . "GraphRAG" . . "HippoRAG" . . "Knowledge Graph Prompting (KGP)" . . "MemWalker" . . . "This pipeline describes the process of constructing and updating the hybrid memory graph from unstructured natural language texts. It leverages LLMs to perform key steps such as formulating vertices and edges, generating hyper-edges, and parsing LLM output into a structured format (e.g., subject-relation-object triples), thereby augmenting KG construction." . "Memorize Pipeline" . . . . "This algorithm integrates the A*, WaterCircles, and BeamSearch strategies within the QA pipeline to enhance extraction efficacy. By combining the outputs of these distinct traversal methods, it aims to improve overall recall and robustness in retrieving information from the knowledge graph, thus contributing to the synergized reasoning of the system." . "Mixed Retrieval Algorithm" . . . "PEARL" . . . "This framework introduces a flexible external memory architecture for LLM agents based on a novel hybrid knowledge graph design (supporting standard edges and two types of hyper-edges: thesis and episodic). It enables rich semantic and temporal representations by allowing LLMs to automatically construct and update this structured memory. This aims to synergize LLM and KG capabilities for a unified knowledge representation that enhances personalized, context-aware reasoning." . "PersonalAI Framework" . . . . "This pipeline handles information search in the memory graph for question answering. It involves an LLM for entity extraction from the natural language question and for generating the final answer, while graph traversal algorithms (like A*, WaterCircles, BeamSearch, and hybrids) are used to retrieve relevant triples from the KG. This exemplifies synergized reasoning by combining LLM capabilities with KG-based structured retrieval." . "QA Pipeline" . . . "ReadAgent" . . "Retrieval-Augmented Generation (RAG)" . . . "This retrieval method is a modified breadth-first search (BFS) algorithm used within the QA pipeline to extract relevant knowledge. It maps query entities to graph vertices, expands outwards, and aggregates triples at intersections, with specific enhancements for handling thesis and episodic hyper-edges, thereby supporting synergized reasoning." . "WaterCircles Retrieval Algorithm" . . . . "2026-02-26T16:26:56.066Z"^^ . . . "LLM-KG assessment for paper 10.48550/arXiv.2506.17001" . "RSA" . "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwNz2QK3SEifno78S7+48zUB0xpTex3mAzW73ZimHqNcdEMU5/apslrGrTHGFAt/Chocgo++r6JQp5ygY7NyJHGWdaIqnt85pjX4PbNfLAvapyUO00qZP34fY61w4eZ9UMtleWEsmZKRtQPyJ8ODl46i/rfPuZlcJGpM9Nmy5mpGWuepqIEvF4a/t7pLVeCEDFSYXT+yaiygt6ynIK5f7TtEDhZpeUf/Q74WhMPJXm4yTU/hqOX4IW+50kWHNArGGZwUaXwzyG6M3Zd6UMModryGkLqS4H/MSE3ZA1Ylnms7BfWLEXhMWlaKi6HRV4nGRDLhxVSi9LSRi3LWKLhNIIQIDAQAB" . "Nl1sCLz4NPJ/eReftK+uU8IF4l6RD2AqzioTLZjgXkj250E/pbAnJD3EaWre8KbeH1+nG8OJASvi9/qSLsMR3j7Mz4Mc028xOmFJTOp7vbK0pbR+KlksqAcIaQmHPHc2sAnwAPiVQwsVdPkW8TERN0Fdk5Bq+h02kuuyOZO2fYJHBKI+hhsB4I5g9OCRcOZ8hwlC5G02KnJlqV6Sr0Hu2GauNgcV6+wXPMfZKRqQrNIN7OEm+4k2rONwEXYKT+Pls9uVaOyz/7Nd3bSRD8Nn0kbI+UbSa04ulSDmA98ng0FjAxyLzYDugl7RqzAqm7C4LABYk8aDISnTuTdFIgnorQ==" . . .