Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs

arXiv:2608.30437 · cs.CL · Submitted 2026-08-31 · Read on arXiv

cs.CL

Submitted: 2026-08-31

Updated: 2026-09-01

Code: https://github.com/dogeee-debug/S2GE

Terminology

• Alignment — 15× in this paper · explained in 1 episode
• Accuracy — 9× in this paper · explained in 1 episode
• RAG — 9× in this paper · explained in 3 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Core — 6× in this paper · explained in 2 episodes
• Knowledge Graph — 6× in this paper · explained in 7 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Tokenization — 4× in this paper · explained in 2 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Adjacency Matrix — 3× in this paper · explained in 1 episode
• Benchmarking — 3× in this paper · explained in 3 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Knowledge graphs — 3× in this paper · explained in 2 episodes
• AUROC — 2× in this paper · explained in 2 episodes
• Adaptive Reasoning — 2× in this paper · explained in 2 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Reasoning Traces — 2× in this paper · explained in 3 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Adaptive Graph — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
• Retrieval-Augmented Generation with Graphs (GraphRAG)
• Graph Foundation Models: A Comprehensive Survey
• A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation Learning
• A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models
• Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding

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