Model-Level GNN Explanations via Rule-to-Graph Readout for Logit Reconstruction
Fuente:
arXiv
Saved in:
| Main Authors: | Lu, Shengyao, Yang, Jiuding, DeFrates, Aedan J., Mills, Keith G., Li, Baochun, Niu, Di |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
by: Lu, Shengyao, et al.
Published: (2024)
by: Lu, Shengyao, et al.
Published: (2024)
Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence
by: Ghasemabadi, Amirhosein, et al.
Published: (2025)
by: Ghasemabadi, Amirhosein, et al.
Published: (2025)
TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution
by: Yang, Jiuding, et al.
Published: (2024)
by: Yang, Jiuding, et al.
Published: (2024)
GOAt: Explaining Graph Neural Networks via Graph Output Attribution
by: Lu, Shengyao, et al.
Published: (2024)
by: Lu, Shengyao, et al.
Published: (2024)
PerfCoder: Large Language Models for Interpretable Code Performance Optimization
by: Yang, Jiuding, et al.
Published: (2025)
by: Yang, Jiuding, et al.
Published: (2025)
rSIM: Incentivizing Reasoning Capabilities of LLMs via Reinforced Strategy Injection
by: Chen, Sijia, et al.
Published: (2025)
by: Chen, Sijia, et al.
Published: (2025)
Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
by: Chen, Sijia, et al.
Published: (2024)
by: Chen, Sijia, et al.
Published: (2024)
Building Optimal Neural Architectures using Interpretable Knowledge
by: Mills, Keith G., et al.
Published: (2024)
by: Mills, Keith G., et al.
Published: (2024)
Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants
by: Yang, Jiuding, et al.
Published: (2024)
by: Yang, Jiuding, et al.
Published: (2024)
Instruction Fusion: Advancing Prompt Evolution through Hybridization
by: Guo, Weidong, et al.
Published: (2023)
by: Guo, Weidong, et al.
Published: (2023)
Applying Graph Explanation to Operator Fusion
by: Mills, Keith G., et al.
Published: (2024)
by: Mills, Keith G., et al.
Published: (2024)
Understanding Expressivity of GNN in Rule Learning
by: Qiu, Haiquan, et al.
Published: (2023)
by: Qiu, Haiquan, et al.
Published: (2023)
On the Consistency of GNN Explanations for Malware Detection
by: Shokouhinejad, Hossein, et al.
Published: (2025)
by: Shokouhinejad, Hossein, et al.
Published: (2025)
Rule2Text: Natural Language Explanation of Logical Rules in Knowledge Graphs
by: Shirvani-Mahdavi, Nasim, et al.
Published: (2025)
by: Shirvani-Mahdavi, Nasim, et al.
Published: (2025)
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
by: Chen, Sijia, et al.
Published: (2024)
by: Chen, Sijia, et al.
Published: (2024)
Graph Reconstruction from Differentially Private GNN Explanations
by: Sahoo, Rishi Raj, et al.
Published: (2026)
by: Sahoo, Rishi Raj, et al.
Published: (2026)
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
by: Yu, Zhaoning, et al.
Published: (2024)
by: Yu, Zhaoning, et al.
Published: (2024)
QGShap: Quantum Acceleration for Faithful GNN Explanations
by: Jena, Haribandhu, et al.
Published: (2025)
by: Jena, Haribandhu, et al.
Published: (2025)
Steering Language Models Before They Speak: Logit-Level Interventions
by: An, Hyeseon, et al.
Published: (2026)
by: An, Hyeseon, et al.
Published: (2026)
GCFX: Generative Counterfactual Explanations for Deep Graph Models at the Model Level
by: Hu, Jinlong, et al.
Published: (2026)
by: Hu, Jinlong, et al.
Published: (2026)
GNN Explanations that do not Explain and How to find Them
by: Azzolin, Steve, et al.
Published: (2026)
by: Azzolin, Steve, et al.
Published: (2026)
On Trustworthy Rule-Based Models and Explanations
by: Siala, Mohamed, et al.
Published: (2025)
by: Siala, Mohamed, et al.
Published: (2025)
Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules
by: Shirvani-Mahdavi, Nasim, et al.
Published: (2025)
by: Shirvani-Mahdavi, Nasim, et al.
Published: (2025)
VickreyFeedback: Cost-efficient Data Construction for Reinforcement Learning from Human Feedback
by: Zhang, Guoxi, et al.
Published: (2024)
by: Zhang, Guoxi, et al.
Published: (2024)
Federated Progressive Self-Distillation with Logits Calibration for Personalized IIoT Edge Intelligence
by: Wang, Yingchao, et al.
Published: (2024)
by: Wang, Yingchao, et al.
Published: (2024)
Why Self-Inconsistency Arises in GNN Explanations and How to Exploit It
by: Tai, Wenxin, et al.
Published: (2026)
by: Tai, Wenxin, et al.
Published: (2026)
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
by: Wang, Xiaoqi, et al.
Published: (2022)
by: Wang, Xiaoqi, et al.
Published: (2022)
FedReview: A Review Mechanism for Rejecting Poisoned Updates in Federated Learning
by: Zheng, Tianhang, et al.
Published: (2024)
by: Zheng, Tianhang, et al.
Published: (2024)
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
by: Yan, Qi, et al.
Published: (2023)
by: Yan, Qi, et al.
Published: (2023)
Abductive and Contrastive Explanations for Scoring Rules in Voting
by: Contet, Clément, et al.
Published: (2024)
by: Contet, Clément, et al.
Published: (2024)
Generating Graph-like Rules for Knowledge Graph Reasoning via Diffusion Models
by: Cheng, Haoxiang, et al.
Published: (2026)
by: Cheng, Haoxiang, et al.
Published: (2026)
DistShap: Scalable GNN Explanations with Distributed Shapley Values
by: Akkas, Selahattin, et al.
Published: (2025)
by: Akkas, Selahattin, et al.
Published: (2025)
FP4DiT: Towards Effective Floating Point Quantization for Diffusion Transformers
by: Chen, Ruichen, et al.
Published: (2025)
by: Chen, Ruichen, et al.
Published: (2025)
Pointwise-in-Time Explanation for Linear Temporal Logic Rules
by: Brindise, Noel, et al.
Published: (2023)
by: Brindise, Noel, et al.
Published: (2023)
Leveraging Association Rules for Better Predictions and Better Explanations
by: Audemard, Gilles, et al.
Published: (2025)
by: Audemard, Gilles, et al.
Published: (2025)
AI Model Modulation with Logits Redistribution
by: Wang, Zihan, et al.
Published: (2026)
by: Wang, Zihan, et al.
Published: (2026)
GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback
by: Xu, Ruiyao, et al.
Published: (2026)
by: Xu, Ruiyao, et al.
Published: (2026)
AL-GNN: Privacy-Preserving and Replay-Free Continual Graph Learning via Analytic Learning
by: Zhang, Xuling, et al.
Published: (2025)
by: Zhang, Xuling, et al.
Published: (2025)
An Empirical Study and Theoretical Explanation on Task-Level Model-Merging Collapse
by: Cao, Yuan, et al.
Published: (2026)
by: Cao, Yuan, et al.
Published: (2026)
Multi-Level Explanations for Generative Language Models
by: Paes, Lucas Monteiro, et al.
Published: (2024)
by: Paes, Lucas Monteiro, et al.
Published: (2024)
Similar Items
-
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
by: Lu, Shengyao, et al.
Published: (2024) -
Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence
by: Ghasemabadi, Amirhosein, et al.
Published: (2025) -
TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution
by: Yang, Jiuding, et al.
Published: (2024) -
GOAt: Explaining Graph Neural Networks via Graph Output Attribution
by: Lu, Shengyao, et al.
Published: (2024) -
PerfCoder: Large Language Models for Interpretable Code Performance Optimization
by: Yang, Jiuding, et al.
Published: (2025)