{"total":57,"rows":[{"id":"2501.00309","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","created":"2024-12-31","cited_by_count":172,"area":"rag"},{"id":"2502.00829","title":"When Do LLMs Help With Node Classification? A Comprehensive Analysis","created":"2025-02-02","cited_by_count":21,"area":null},{"id":"2601.22384","title":"Graph is a Substrate Across Data Modalities","created":"2026-01-29","cited_by_count":14,"area":null},{"id":"2509.22416","title":"One Prompt Fits All: Universal Graph Adaptation for Pretrained Models","created":"2025-09-26","cited_by_count":11,"area":null},{"id":"2412.12456","title":"Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks","created":"2024-12-17","cited_by_count":10,"area":null},{"id":"2604.19028","title":"Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors","created":"2026-04-21","cited_by_count":10,"area":null},{"id":"2502.11836","title":"Model Generalization on Text Attribute Graphs: Principles with Large Language Models","created":"2025-02-17","cited_by_count":8,"area":null},{"id":"2505.02130","title":"Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data","created":"2025-05-04","cited_by_count":8,"area":null},{"id":"2410.11370","title":"Enhance Graph Alignment for Large Language Models","created":"2024-10-15","cited_by_count":7,"area":"alignment"},{"id":"2504.10917","title":"Towards A Universal Graph Structural Encoder","created":"2025-04-15","cited_by_count":7,"area":null},{"id":"2510.16885","title":"UniGTE: Unified Graph-Text Encoding for Zero-Shot Generalization across Graph Tasks and Domains","created":"2025-10-19","cited_by_count":7,"area":null},{"id":"2602.04116","title":"Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach","created":"2026-02-04","cited_by_count":7,"area":null},{"id":"2603.01385","title":"Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning","created":"2026-03-02","cited_by_count":7,"area":null},{"id":"2506.07334","title":"Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models","created":"2025-06-09","cited_by_count":6,"area":"inference"},{"id":"2512.21106","title":"Semantic Refinement with LLMs for Graph Representations","created":"2025-12-24","cited_by_count":6,"area":null},{"id":"2505.17599","title":"Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs","created":"2025-05-23","cited_by_count":3,"area":null},{"id":"2603.13434","title":"Modality-free Graph In-context Alignment","created":"2026-03-13","cited_by_count":3,"area":null},{"id":"2605.09993","title":"Learning Graph Foundation Models on Riemannian Graph-of-Graphs","created":"2026-05-11","cited_by_count":3,"area":null},{"id":"2412.01849","title":"Towards Data-centric Machine Learning on Directed Graphs: a Survey","created":"2024-11-28","cited_by_count":2,"area":null},{"id":"2412.08038","title":"Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach","created":"2024-12-11","cited_by_count":2,"area":"synth"},{"id":"2503.11086","title":"A Survey of Cross-domain Graph Learning: Progress and Future Directions","created":"2025-03-14","cited_by_count":2,"area":null},{"id":"2510.04567","title":"GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning","created":"2025-10-06","cited_by_count":2,"area":null},{"id":"2510.16769","title":"See or Say Graphs: Agent-Driven Scalable Graph Structure Understanding with Vision-Language Models","created":"2025-10-19","cited_by_count":2,"area":"mllm"},{"id":"2601.21369","title":"Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach","created":"2026-01-29","cited_by_count":2,"area":"lr"},{"id":"2605.03514","title":"Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding","created":"2026-05-05","cited_by_count":2,"area":null},{"id":"2410.16822","title":"Can Large Language Models Act as Ensembler for Multi-GNNs?","created":"2024-10-22","cited_by_count":1,"area":null},{"id":"2505.12027","title":"Relation-Aware Graph Foundation Model","created":"2025-05-17","cited_by_count":1,"area":null},{"id":"2505.13989","title":"When LLMs meet open-world graph learning: a new perspective for unlabeled data uncertainty","created":"2025-05-20","cited_by_count":1,"area":null},{"id":"2603.02938","title":"Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models","created":"2026-03-03","cited_by_count":1,"area":null},{"id":"2603.14937","title":"LLM as Graph Kernel: Rethinking Message Passing on Text-Rich Graphs","created":"2026-03-16","cited_by_count":1,"area":"lr"},{"id":"2604.15951","title":"Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval","created":"2026-04-17","cited_by_count":1,"area":"lr"},{"id":"2605.13540","title":"Decoupled and Divergence-Conditioned Prompt for Multi-domain Dynamic Graph Foundation Models","created":"2026-05-13","cited_by_count":1,"area":null},{"id":"2605.14809","title":"GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2606.22429","title":"Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation","created":"2026-06-21","cited_by_count":1,"area":null},{"id":"2606.22462","title":"Adaptive Recurrent Message Passing for Test Time Computing on Graphs","created":"2026-06-21","cited_by_count":1,"area":null},{"id":"2607.28980","title":"Beyond Feature and Structure Alignment: Learning Transferable Propagation Knowledge for Graph Foundation Models","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2608.29588","title":"Call Neighbours Yourself: Graph Walks with Destination-Conditioned On-Policy Self-Distillation","created":"2026-08-30","cited_by_count":1,"area":"distill"},{"id":"2506.09738","title":"Towards Multimodal Graph Large Language Model","created":"2025-06-11","cited_by_count":0,"area":null},{"id":"2509.08401","title":"Two Facets of the Same Optimization Coin: Model Degradation and Representation Collapse in Graph Foundation Models","created":"2025-09-10","cited_by_count":0,"area":null},{"id":"2510.08774","title":"Struc-EMB: The Potential of Structure-Aware Encoding in Language Embeddings","created":"2025-10-09","cited_by_count":0,"area":null},{"id":"2601.21067","title":"Out-of-Distribution Generalization in Graph Foundation Models","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2602.04244","title":"GraphVec: Cross-Domain Graph Vectorization for Graph-Level Representation Learning","created":"2026-02-04","cited_by_count":0,"area":null},{"id":"2604.17271","title":"HopRank: Self-Supervised LLM Preference-Tuning on Graphs for Few-Shot Node Classification","created":"2026-04-19","cited_by_count":0,"area":null},{"id":"2604.17897","title":"LoReC: Rethinking Large Language Models for Graph Data Analysis","created":"2026-04-20","cited_by_count":0,"area":"lr"},{"id":"2605.12197","title":"A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.21858","title":"Hypergraph as Language","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2606.11562","title":"GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.11898","title":"GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2607.26023","title":"CHARM: A Multimodal Graph Foundation Model with Hierarchical Context Modeling for Zero-Shot Transfer","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2608.26732","title":"Rethinking Message Passing as Retrieval for Text-Attributed Graph Learning","created":"2026-08-27","cited_by_count":0,"area":"lr"},{"id":"2608.30437","title":"Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.08709","title":"Chimaera: A Mixture-of-Graph-Experts Architecture for Cross-Task and Cross-Dataset Graph Learning","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.23547","title":"Preserving Geometric Integrity in Graph Prompting via Measure-Constrained Optimal Transport","created":"2026-09-20","cited_by_count":0,"area":null},{"id":"2609.30894","title":"Training Graph Foundation Models on The Web Graph","created":"2026-09-25","cited_by_count":0,"area":null},{"id":"2609.33314","title":"ZeroGAR: Benchmarking the Adversarial Robustness of Zero-Shot Graph Models","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.33521","title":"LLM4Trust: Exploring the Capabilities of Large Language Models for Trust Evaluation","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2610.14710","title":"DeKoR: Decomposed Knowledge Routing for Efficient GNN--LLM Fusion","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}