Cover Image

LLM as Clinical Graph Structure Refiner: Enhancing Representation Learning in EEG Seizure Diagnosis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Lincan, Chen, Zheng, Dong, Yushun
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimizing EEG Graph Structure for Seizure Detection: An Information Bottleneck and Self-Supervised Learning Approach
by: Li, Lincan, et al.
Published: (2026)

Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses
by: Li, Lincan, et al.
Published: (2025)

Graph-level Protein Representation Learning by Structure Knowledge Refinement
by: Wang, Ge, et al.
Published: (2024)

Disentangle-then-Refine: LLM-Guided Decoupling and Structure-Aware Refinement for Graph Contrastive Learning
by: Li, Zhaoxing, et al.
Published: (2026)

A Survey on Model Extraction Attacks and Defenses for Large Language Models
by: Zhao, Kaixiang, et al.
Published: (2025)

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives
by: Zhao, Kaixiang, et al.
Published: (2025)

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
by: Zhao, Kaixiang, et al.
Published: (2025)

Long-Term EEG Partitioning for Seizure Onset Detection
by: Chen, Zheng, et al.
Published: (2024)

STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model
by: Li, Lincan, et al.
Published: (2024)

Epileptic Seizure Detection and Prediction from EEG Data: A Machine Learning Approach with Clinical Validation
by: Jayanti, Ria, et al.
Published: (2025)

TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series
by: Piao, Xihao, et al.
Published: (2026)

Knowledge Graph-Enhanced Large Language Models via Path Selection
by: Liu, Haochen, et al.
Published: (2024)

DistilCLIP-EEG: Enhancing Epileptic Seizure Detection Through Multi-modal Learning and Knowledge Distillation
by: Wang, Zexin, et al.
Published: (2025)

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
by: Li, Wenliang, et al.
Published: (2025)

Supervised and Unsupervised Deep Learning Approaches for EEG Seizure Prediction
by: Georgis-Yap, Zakary, et al.
Published: (2023)

Refine Medical Diagnosis Using Generation Augmented Retrieval and Clinical Practice Guidelines
by: Li, Wenhao, et al.
Published: (2025)

ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation
by: Kotoge, Rikuto, et al.
Published: (2025)

EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild
by: Dai, Yuyang, et al.
Published: (2026)

LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs
by: Ma, Xiaoxu, et al.
Published: (2026)

Disentangling Multiplex Spatial-Temporal Transition Graph Representation Learning for Socially Enhanced POI Recommendation
by: Li, Jie, et al.
Published: (2025)

RAICL: Retrieval-Augmented In-Context Learning for Vision-Language-Model Based EEG Seizure Detection
by: Li, Siyang, et al.
Published: (2026)

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
by: Chen, Zihan, et al.
Published: (2025)

KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models
by: Zheng, Zaiyi, et al.
Published: (2025)

Semantic Refinement with LLMs for Graph Representations
by: Thapaliya, Safal, et al.
Published: (2025)

ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data
by: Lei, Zhenyu, et al.
Published: (2024)

Accuracy-Constrained CNN Pruning for Efficient and Reliable EEG-Based Seizure Detection
by: K, Mounvik, et al.
Published: (2025)

Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement
by: Ying, Wangyang, et al.
Published: (2026)

Rethinking Fair Graph Neural Networks from Re-balancing
by: Li, Zhixun, et al.
Published: (2024)

Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
by: Dong, Yushun, et al.
Published: (2024)

Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments
by: Liang, Yile, et al.
Published: (2024)

A Hybrid Graph Neural Network for Enhanced EEG-Based Depression Detection
by: Wang, Yiye, et al.
Published: (2024)

Learn to Think: Bootstrapping LLM Reasoning Capability Through Graph Representation Learning
by: Gao, Hang, et al.
Published: (2025)

EEGDM: Learning EEG Representation with Latent Diffusion Model
by: Wang, Shaocong, et al.
Published: (2025)

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models
by: Cheng, Xueqi, et al.
Published: (2025)

Atoms of Thought: Universal EEG Representation Learning with Microstates
by: Tian, Xinyang, et al.
Published: (2026)

EEG-DIF: Early Warning of Epileptic Seizures through Generative Diffusion Model-based Multi-channel EEG Signals Forecasting
by: Jiang, Zekun, et al.
Published: (2024)

CLEF: EEG Foundation Model for Learning Clinical Semantics
by: Cao, Peng, et al.
Published: (2026)

EEG_RL-Net: Enhancing EEG MI Classification through Reinforcement Learning-Optimised Graph Neural Networks
by: Aung, Htoo Wai, et al.
Published: (2024)

Refining Latent Representations: A Generative SSL Approach for Heterogeneous Graph Learning
by: Hu, Yulan, et al.
Published: (2023)

Enhancing LLM Steering through Sparse Autoencoder-Based Vector Refinement
by: Wang, Anyi, et al.
Published: (2025)