Copertina

Retrieval Augmented Generation for Dynamic Graph Modeling

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wu, Yuxia, Liao, Lizi, Fang, Yuan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Exploring the Potential of Large Language Models for Heterophilic Graphs
di: Wu, Yuxia, et al.
Pubblicazione: (2024)

RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation
di: Yuan, Haonan, et al.
Pubblicazione: (2026)

Spectral Surgery: Training-Free Refinement of LoRA via Gradient-Guided Singular Value Reweighting
di: Tian, Zailong, et al.
Pubblicazione: (2026)

Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation
di: Yan, Yuchen, et al.
Pubblicazione: (2025)

RAGraph: A General Retrieval-Augmented Graph Learning Framework
di: Jiang, Xinke, et al.
Pubblicazione: (2024)

On the Feasibility of Simple Transformer for Dynamic Graph Modeling
di: Wu, Yuxia, et al.
Pubblicazione: (2024)

Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
di: Prahlad, Deeksha, et al.
Pubblicazione: (2025)

Source Attribution in Retrieval-Augmented Generation
di: Nematov, Ikhtiyor, et al.
Pubblicazione: (2025)

Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs
di: Zhang, Haozhen, et al.
Pubblicazione: (2024)

Less is More: Denoising Knowledge Graphs For Retrieval Augmented Generation
di: Zheng, Yilun, et al.
Pubblicazione: (2025)

AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMs
di: Wang, Yubo, et al.
Pubblicazione: (2025)

Learning from History: A Retrieval-Augmented Framework for Spatiotemporal Prediction
di: Jia, Hao, et al.
Pubblicazione: (2025)

KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation
di: Chen, Qizhi, et al.
Pubblicazione: (2026)

DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
di: Xiao, Yongkang, et al.
Pubblicazione: (2025)

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation
di: Zhu, Yuqicheng, et al.
Pubblicazione: (2025)

Quantizing Text-attributed Graphs for Semantic-Structural Integration
di: Bo, Jianyuan, et al.
Pubblicazione: (2025)

HoReN: Normalized Hopfield Retrieval for Large-Scale Sequential Model Editing
di: Fang, Yuan, et al.
Pubblicazione: (2026)

Latent Retrieval Augmented Generation of Cross-Domain Protein Binders
di: Zhang, Zishen, et al.
Pubblicazione: (2025)

RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios
di: Ding, Wenhao, et al.
Pubblicazione: (2023)

Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models
di: Peng, Zhiyuan, et al.
Pubblicazione: (2023)

Adaptive Spatiotemporal Augmentation for Improving Dynamic Graph Learning
di: Chu, Xu, et al.
Pubblicazione: (2025)

A Graph-Retrieval-Augmented Generation Framework Enhances Decision-Making in the Circular Economy
di: Zhao, Yang, et al.
Pubblicazione: (2025)

XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation
di: Li, Zhuoling, et al.
Pubblicazione: (2026)

Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model
di: Tian, Yuxing, et al.
Pubblicazione: (2024)

LLM-Powered Text-Attributed Graph Anomaly Detection via Retrieval-Augmented Reasoning
di: Xu, Haoyan, et al.
Pubblicazione: (2025)

DynaGRAG | Exploring the Topology of Information for Advancing Language Understanding and Generation in Graph Retrieval-Augmented Generation
di: Thakrar, Karishma
Pubblicazione: (2024)

Event-Aware Prompt Learning for Dynamic Graphs
di: Yu, Xingtong, et al.
Pubblicazione: (2025)

Large Language Model Agent for Structural Drawing Generation Using ReAct Prompt Engineering and Retrieval Augmented Generation
di: Zhang, Xin, et al.
Pubblicazione: (2025)

Bridge: Retrieval-Augmented Spatiotemporal Modeling for Urban Delivery Demand
di: Tang, Yihong, et al.
Pubblicazione: (2026)

CORE: Contrastive Masked Feature Reconstruction on Graphs
di: Bo, Jianyuan, et al.
Pubblicazione: (2025)

Beyond 9-to-5: A Generative Model for Augmenting Mobility Data of Underrepresented Shift Workers
di: Ma, Haoxuan, et al.
Pubblicazione: (2025)

Tensor Graph Convolutional Network for Dynamic Graph Representation Learning
di: Wang, Ling, et al.
Pubblicazione: (2024)

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
di: Yan, Qi, et al.
Pubblicazione: (2023)

Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation
di: Qi, Jirui, et al.
Pubblicazione: (2024)

RePCS: Diagnosing Data Memorization in LLM-Powered Retrieval-Augmented Generation
di: Anh, Le Vu, et al.
Pubblicazione: (2025)

WixQA: A Multi-Dataset Benchmark for Enterprise Retrieval-Augmented Generation
di: Cohen, Dvir, et al.
Pubblicazione: (2025)

RAGuard: A Novel Approach for in-context Safe Retrieval Augmented Generation for LLMs
di: Walker, Connor, et al.
Pubblicazione: (2025)

TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster
di: Ning, Kanghui, et al.
Pubblicazione: (2025)

Learning Retrieval Augmentation for Personalized Dialogue Generation
di: Huang, Qiushi, et al.
Pubblicazione: (2024)

Multiple Abstraction Level Retrieve Augment Generation
di: Zheng, Zheng, et al.
Pubblicazione: (2025)