. . . . "GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding" . . . . . . . . . . . "Few-Shot Prompting" . . . "This method leverages the LLM's generative capabilities to rewrite or summarize the encoded graph statements into more coherent representations for fine-tuning. The goal is to enhance semantic alignment between the KG and the LLM's vocabulary, thereby improving the LLM's factual recall and multi-hop reasoning after training." . "GLaM (LLM Summarization)" . . . . "This method combines multiple encoding strategies, specifically using LLM's zero-shot capabilities to create text-based node descriptors from the k-hop context subgraph, utilizing adjacency lists, and performing summarization. This comprehensive approach aims to instill robust graph-based reasoning capabilities into the LLM via fine-tuning." . "GLaM (Node Descriptors, Adjacency Lists, and Summarization Combination)" . . . . "This GLaM variant encodes the neighborhood subgraph by including the entire adjacency list of the central node or partitioning neighbors based on relation types. This strategy is used to fine-tune the LLM to better understand graph structure for improved knowledge expression." . "GLaM (Relational Grouping)" . . . . "This method is a specific implementation within the GLaM framework where the neighborhood subgraph is encoded into (source, relation, target) triples for fine-tuning. It aims to improve the LLM's factual reasoning by embedding graph knowledge directly into its parameters during the training phase." . "GLaM (Triples)" . . . "GNN-LLM Joint Model Coupling" . . "GNN-LLM Soft Prompting" . . "Retrieval Augmented Generation (RAG)" . . . "2026-02-26T15:57:20.083Z"^^ . . . "LLM-KG assessment for paper 10.48550/arXiv.2402.06764" . "RSA" . "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwNz2QK3SEifno78S7+48zUB0xpTex3mAzW73ZimHqNcdEMU5/apslrGrTHGFAt/Chocgo++r6JQp5ygY7NyJHGWdaIqnt85pjX4PbNfLAvapyUO00qZP34fY61w4eZ9UMtleWEsmZKRtQPyJ8ODl46i/rfPuZlcJGpM9Nmy5mpGWuepqIEvF4a/t7pLVeCEDFSYXT+yaiygt6ynIK5f7TtEDhZpeUf/Q74WhMPJXm4yTU/hqOX4IW+50kWHNArGGZwUaXwzyG6M3Zd6UMModryGkLqS4H/MSE3ZA1Ylnms7BfWLEXhMWlaKi6HRV4nGRDLhxVSi9LSRi3LWKLhNIIQIDAQAB" . "u6dPlUuTUn1QedW6Fo7ljSYw2G4COewda0DpI0s95BWkF2vMzjoMKMokBVugNbLAF7WgBfWLNdwTqbnSBYf9xRted+aca4PBWgEF/7gswieTkJn0cmbIkRP85Fl+j9VWoAgVzb4c5Zu8KcI3cXo5W7LLfNx6yCW1fgamArf4JmksrxJIsftt9gcgHTJKFMt3XsI0WBTmVF3hcrJqj4tf/vAOIiuEnHkcMK2hOk4+0BAjf9MXAKG1b5ufatAxOHCQxqwe4dTz7da/ClVar+D0yMszjGQHpWfsEPcVvWz6hxmK2/0PueA/cKu4mrpSyACehPyNjjEwIqWSKn/XqMqzCg==" . . .