. . . . "GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning" . . . . . . . . . . . . . . . "G-Retriever" . . "https://github.com/cmavro/ReaRev_KGQA"^^ . . "GNN-RAG enhances LLM performance on KGQA by using a GNN to retrieve relevant multi-hop reasoning paths from a KG. These verbalized paths are then fed to the LLM as context for RAG, thereby improving the LLM's ability to answer complex questions during its inference stage and reducing hallucinations." . "GNN-RAG" . . . "https://github.com/cmavro/ReaRev_KGQA"^^ . . "GNN-RAG+RA further boosts LLM KGQA performance by employing retrieval augmentation, combining GNN-induced reasoning paths with LLM-based retrieved paths (e.g., from RoG). This method increases the diversity and recall of retrieved KG information, which in turn enhances the LLM's reasoning and answer accuracy during inference." . "GNN-RAG+RA" . . . "GraftNet" . . "KB-BINDER" . . "KD-CoT" . . "LM SR" . . "NSM" . . "ReaRev" . . "RoG" . . "SBERT" . . "ToG" . . . "2026-02-26T16:19:24.245Z"^^ . . . "LLM-KG assessment for paper 10.48550/arXiv.2405.20139" . "RSA" . "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwNz2QK3SEifno78S7+48zUB0xpTex3mAzW73ZimHqNcdEMU5/apslrGrTHGFAt/Chocgo++r6JQp5ygY7NyJHGWdaIqnt85pjX4PbNfLAvapyUO00qZP34fY61w4eZ9UMtleWEsmZKRtQPyJ8ODl46i/rfPuZlcJGpM9Nmy5mpGWuepqIEvF4a/t7pLVeCEDFSYXT+yaiygt6ynIK5f7TtEDhZpeUf/Q74WhMPJXm4yTU/hqOX4IW+50kWHNArGGZwUaXwzyG6M3Zd6UMModryGkLqS4H/MSE3ZA1Ylnms7BfWLEXhMWlaKi6HRV4nGRDLhxVSi9LSRi3LWKLhNIIQIDAQAB" . "BKsB5zCOEzTtCoNJXfgkuVcii70xQEEIZvULiMb7TOExh+jgJZmVp87Witiqu7hPU3K4GTylk5Tp5HVNrpvC8e69ReYOY61xQ5lT+VX/ZUhb2FazXHRyZxPL1ARcVYsQfSKstOKRT6ycrm0iDRXYwbUpCpdc1eVQMOMitTdAEpAU2VdsOK/8KUKHNuiiLaDMG8bA7w3G5GCrovB1TKBUjssZSzA4IpzSk5xRm3o3q6gSavmRcnZFIQlxbv2Vaqp+mTR11RYHDglRXf5yrUbzRv5hgKOO+u6BCOPiD/Y+khvj2gsvniKj/XEbnvw4e3lcMs3XXU+ju7F35A9fPTXLEg==" . . .