Copertina

The Final Layer Holds the Key: A Unified and Efficient GNN Calibration Framework

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Huang, Jincheng, Xu, Jie, Shi, Xiaoshuang, Hu, Ping, Feng, Lei, Zhu, Xiaofeng
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks
di: Huang, Jincheng, et al.
Pubblicazione: (2024)

Efficient Link Prediction via GNN Layers Induced by Negative Sampling
di: Wang, Yuxin, et al.
Pubblicazione: (2023)

Isotonic Layer: A Unified Framework for Recommendation Calibration and Debiasing
di: Cheng, Hailing, et al.
Pubblicazione: (2026)

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
di: Jiang, Haitian, et al.
Pubblicazione: (2023)

A Cross-graph Tuning-free GNN Prompting Framework
di: Chen, Yaqi, et al.
Pubblicazione: (2026)

GNN-based Unified Deep Learning
di: Pala, Furkan, et al.
Pubblicazione: (2025)

SliceGX: Layer-wise GNN Explanation with Model-slicing
di: Zhu, Tingting, et al.
Pubblicazione: (2025)

Calibrating and Rotating: A Unified Framework for Weight Conditioning in PEFT
di: Chang, Da, et al.
Pubblicazione: (2025)

Provably Convergent Subgraph-wise Sampling for Fast GNN Training
di: Wang, Jie, et al.
Pubblicazione: (2023)

BOASF: A Unified Framework for Speeding up Automatic Machine Learning via Adaptive Successive Filtering
di: Zhu, Guanghui, et al.
Pubblicazione: (2025)

COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees
di: Wang, Zhiyuan, et al.
Pubblicazione: (2025)

SConU: Selective Conformal Uncertainty in Large Language Models
di: Wang, Zhiyuan, et al.
Pubblicazione: (2025)

Calibrated Principal Component Regression
di: Wu, Yixuan Florence, et al.
Pubblicazione: (2025)

FastGL: A GPU-Efficient Framework for Accelerating Sampling-Based GNN Training at Large Scale
di: Zhu, Zeyu, et al.
Pubblicazione: (2024)

GraphPL: Leveraging GNN for Efficient and Robust Modalities Imputation in Patchwork Learning
di: Hu, Xingjian, et al.
Pubblicazione: (2026)

SmoothGNN: Smoothing-aware GNN for Unsupervised Node Anomaly Detection
di: Dong, Xiangyu, et al.
Pubblicazione: (2024)

ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs
di: Lu, Weigang, et al.
Pubblicazione: (2025)

Panther: A Cost-Effective Privacy-Preserving Framework for GNN Training and Inference Services in Cloud Environments
di: Chen, Congcong, et al.
Pubblicazione: (2025)

Unified Uncertainty Calibration
di: Chaudhuri, Kamalika, et al.
Pubblicazione: (2023)

DFedReweighting: A Unified Framework for Objective-Oriented Reweighting in Decentralized Federated Learning
di: Zhang, Kaichuang, et al.
Pubblicazione: (2025)

GSR-GNN: Training Acceleration and Memory-Saving Framework of Deep GNNs on Circuit Graph
di: Luo, Yuebo, et al.
Pubblicazione: (2026)

Adaptive Graph Coarsening for Efficient GNN Training
di: Olshevskyi, Rostyslav, et al.
Pubblicazione: (2025)

Efficient Jailbreaking of Large Models by Freeze Training: Lower Layers Exhibit Greater Sensitivity to Harmful Content
di: Shen, Hongyuan, et al.
Pubblicazione: (2025)

A Unified Geometric Field Theory Framework for Transformers: From Manifold Embeddings to Kernel Modulation
di: Shi, Xianshuai, et al.
Pubblicazione: (2025)

A Unified Multi-Agent Framework for Universal Multimodal Understanding and Generation
di: Li, Jiulin, et al.
Pubblicazione: (2025)

Global-Graph Guided and Local-Graph Weighted Contrastive Learning for Unified Clustering on Incomplete and Noise Multi-View Data
di: He, Hongqing, et al.
Pubblicazione: (2025)

Deep Learning-Enhanced Calibration of the Heston Model: A Unified Framework
di: Zadgar, Arman, et al.
Pubblicazione: (2025)

GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs
di: Zhu, Zhongshu, et al.
Pubblicazione: (2024)

Vehicle-as-Prompt: A Unified Deep Reinforcement Learning Framework for Heterogeneous Fleet Vehicle Routing Problem
di: Huang, Shihong, et al.
Pubblicazione: (2026)

LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges
di: Cheng, Xu, et al.
Pubblicazione: (2025)

EUGens: Efficient, Unified, and General Dense Layers
di: Kim, Sang Min, et al.
Pubblicazione: (2026)

All Nodes are created Not Equal: Node-Specific Layer Aggregation and Filtration for GNN
di: Wang, Shilong, et al.
Pubblicazione: (2024)

LayerT2V: A Unified Multi-Layer Video Generation Framework
di: Li, Guangzhao, et al.
Pubblicazione: (2025)

An Efficient Subgraph GNN with Provable Substructure Counting Power
di: Yan, Zuoyu, et al.
Pubblicazione: (2023)

LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture
di: Li, Yanhui, et al.
Pubblicazione: (2025)

NestGNN: A Graph Neural Network Framework Generalizing the Nested Logit Model for Travel Mode Choice
di: Zhou, Yuqi, et al.
Pubblicazione: (2025)

MLKV: Multi-Layer Key-Value Heads for Memory Efficient Transformer Decoding
di: Zuhri, Zayd Muhammad Kawakibi, et al.
Pubblicazione: (2024)

A Unified Gradient-based Framework for Task-agnostic Continual Learning-Unlearning
di: Huang, Zhehao, et al.
Pubblicazione: (2025)

A Unified Framework for Knowledge Transfer in Bidirectional Model Scaling
di: Shen, Jianlu, et al.
Pubblicazione: (2026)

On the Robustness of Graph Reduction Against GNN Backdoor
di: Zhu, Yuxuan, et al.
Pubblicazione: (2024)