Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning

arXiv:2605.10247 · cs.LG · Submitted 2026-05-11 · Read on arXiv

cs.LG

Submitted: 2026-05-11

Updated: 2026-10-02

Code: https://github.com/DarioVajda/graph_model

Terminology

• Benchmark — 1× in this paper · explained in 2 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 3 episodes
• Graph Transformer Language Model — 1× in this paper
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Structural Reasoning — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• LLaGA: Large Language and Graph Assistant
• Gemma 3 Technical Report
• LoRA: Low-Rank Adaptation of Large Language Models
• Semi-Supervised Classification with Graph Convolutional Networks
• Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation
• Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
• Graph Inductive Biases in Transformers without Message Passing
• GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning
• The Llama 3 Herd of Models
• Let Your Graph Do the Talking: Encoding Structured Data for LLMs
• Molecular Representations for Large Language Models
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
• RoFormer: Enhanced Transformer with Rotary Position Embedding
• MoleculeNet: A Benchmark for Molecular Machine Learning
• A Survey of Graph Transformers: Architectures, Theories and Applications
• Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning
• Deep Graph Contrastive Representation Learning

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