Cover Image

PowerGraph-LLM: Novel Power Grid Graph Embedding and Optimization with Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bernier, Fabien, Cao, Jun, Cordy, Maxime, Ghamizi, Salah
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can Large Language Models Reason and Optimize Under Constraints?
by: Bernier, Fabien, et al.
Published: (2026)

SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids
by: Ghamizi, Salah, et al.
Published: (2024)

SafePowerGraph-HIL: Real-Time HIL Validation of Heterogeneous GNNs for Bridging Sim-to-Real Gap in Power Grids
by: Ma, Aoxiang, et al.
Published: (2025)

Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability
by: Ky, Joël Roman, et al.
Published: (2026)

Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks
by: Bernier, Fabien, et al.
Published: (2025)

Robustness Analysis of AI Models in Critical Energy Systems
by: Dogoulis, Pantelis, et al.
Published: (2024)

Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories
by: Dogoulis, Pantelis, et al.
Published: (2025)

KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections
by: Dogoulis, Pantelis, et al.
Published: (2025)

TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
by: Simonetto, Thibault, et al.
Published: (2024)

Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data
by: Simonetto, Thibault, et al.
Published: (2024)

RobustBlack: Challenging Black-Box Adversarial Attacks on State-of-the-Art Defenses
by: Djilani, Mohamed, et al.
Published: (2024)

Test Time Training for AC Power Flow Surrogates via Physics and Operational Constraint Refinement
by: Dogoulis, Panteleimon, et al.
Published: (2025)

Fault Diagnosis in Power Grids with Large Language Model
by: Jing, Liu, et al.
Published: (2024)

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
by: He, Yingzhi, et al.
Published: (2025)

On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing
by: Dong, Zeming, et al.
Published: (2022)

Graph-Enhanced Model-Free Reinforcement Learning Agents for Efficient Power Grid Topological Control
by: Batanero, Eloy Anguiano, et al.
Published: (2025)

LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model
by: Lin, Tianqianjin, et al.
Published: (2024)

LLM-Powered Knowledge Graphs for Enterprise Intelligence and Analytics
by: Kumar, Rajeev, et al.
Published: (2025)

Physics Informed Reinforcement Learning with Gibbs Priors for Topology Control in Power Grids
by: Dogoulis, Pantelis, et al.
Published: (2026)

Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis
by: Akli, Amal, et al.
Published: (2026)

Grid-Agent: An LLM-Powered Multi-Agent System for Power Grid Control
by: Zhang, Yan, et al.
Published: (2025)

X-GridAgent: An LLM-Powered Agentic AI System for Assisting Power Grid Analysis
by: Yihan, et al.
Published: (2025)

Graph Embedding Dynamic Feature-based Supervised Contrastive Learning of Transient Stability for Changing Power Grid Topologies
by: Lv, Zijian, et al.
Published: (2023)

GraphReason: Enhancing Reasoning Capabilities of Large Language Models through A Graph-Based Verification Approach
by: Cao, Lang
Published: (2023)

Large Language Model Powered Decision Support for a Metal Additive Manufacturing Knowledge Graph
by: Khan, Muhammad Tayyab, et al.
Published: (2025)

On The Expressive Power of Knowledge Graph Embedding Methods
by: Gao, Jiexing, et al.
Published: (2024)

Large Language Models for Knowledge Graph Embedding: A Survey
by: Liu, Bingchen, et al.
Published: (2025)

Proximal Policy Optimization with Graph Neural Networks for Optimal Power Flow
by: López-Cardona, Ángela, et al.
Published: (2022)

Insights on Adversarial Attacks for Tabular Machine Learning via a Systematic Literature Review
by: Dyrmishi, Salijona, et al.
Published: (2025)

Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
by: Liu, Boming, et al.
Published: (2026)

PowerGraph: A power grid benchmark dataset for graph neural networks
by: Varbella, Anna, et al.
Published: (2024)

GridCodex: A RAG-Driven AI Framework for Power Grid Code Reasoning and Compliance
by: Shi, Jinquan, et al.
Published: (2025)

GridMind: LLMs-Powered Agents for Power System Analysis and Operations
by: Jin, Hongwei, et al.
Published: (2025)

LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
by: BehnamGhader, Parishad, et al.
Published: (2024)

PLDR-LLM: Large Language Model from Power Law Decoder Representations
by: Gokden, Burc
Published: (2024)

On the Expressive Power of Graph Neural Networks
by: Nalwade, Ashwin, et al.
Published: (2024)

One Model, Many Skills: Parameter-Efficient Fine-Tuning for Multitask Code Analysis
by: Akli, Amal, et al.
Published: (2026)

ElecBench: a Power Dispatch Evaluation Benchmark for Large Language Models
by: Zhou, Xiyuan, et al.
Published: (2024)

Toward Dynamic Stability Assessment of Power Grid Topologies using Graph Neural Networks
by: Nauck, Christian, et al.
Published: (2022)

Large Language Model-Powered Evolutionary Code Optimization on a Phylogenetic Tree
by: Zhao, Leyi, et al.
Published: (2026)