Saved in:
| Main Authors: | Chen, Chao, Chen, Yanhui, Lin, Shanshan, Hong, Dongsheng, Wu, Shu, Liao, Xiangwen, Liu, Chuanyi |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.01938 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
From Attribution to Action: Jointly ALIGNing Predictions and Explanations
by: Hong, Dongsheng, et al.
Published: (2025)
by: Hong, Dongsheng, et al.
Published: (2025)
BAED: a New Paradigm for Few-shot Graph Learning with Explanation in the Loop
by: Chen, Chao, et al.
Published: (2026)
by: Chen, Chao, et al.
Published: (2026)
Provable Robust Saliency-based Explanations
by: Chen, Chao, et al.
Published: (2022)
by: Chen, Chao, et al.
Published: (2022)
A Survey on Memory-Efficient Transformer-Based Model Training in AI for Science
by: Tian, Kaiyuan, et al.
Published: (2025)
by: Tian, Kaiyuan, et al.
Published: (2025)
Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
by: Zhang, Jiaxing, et al.
Published: (2025)
by: Zhang, Jiaxing, et al.
Published: (2025)
Adversarial Training for Robust Coverage Network under Worst-case Facility Losses
by: Miao, Changhao, et al.
Published: (2026)
by: Miao, Changhao, et al.
Published: (2026)
Interpreting Inflammation Prediction Model via Tag-based Cohort Explanation
by: Meng, Fanyu, et al.
Published: (2024)
by: Meng, Fanyu, et al.
Published: (2024)
Meta Additive Model: Interpretable Sparse Learning With Auto Weighting
by: Zhang, Xuelin, et al.
Published: (2026)
by: Zhang, Xuelin, et al.
Published: (2026)
Learning Robust Reasoning through Guided Adversarial Self-Play
by: Li, Shuozhe, et al.
Published: (2026)
by: Li, Shuozhe, et al.
Published: (2026)
E-ICL: Enhancing Fine-Grained Emotion Recognition through the Lens of Prototype Theory
by: Ren, Zhaochun, et al.
Published: (2024)
by: Ren, Zhaochun, et al.
Published: (2024)
Adversarial Instance Generation and Robust Training for Neural Combinatorial Optimization with Multiple Objectives
by: Liu, Wei, et al.
Published: (2026)
by: Liu, Wei, et al.
Published: (2026)
Ignition Phase : Standard Training for Fast Adversarial Robustness
by: Yu-Hang, Wang, et al.
Published: (2025)
by: Yu-Hang, Wang, et al.
Published: (2025)
Bridging Interpretability and Robustness Using LIME-Guided Model Refinement
by: Nayyem, Navid, et al.
Published: (2024)
by: Nayyem, Navid, et al.
Published: (2024)
Structure-Guided Adversarial Training of Diffusion Models
by: Yang, Ling, et al.
Published: (2024)
by: Yang, Ling, et al.
Published: (2024)
Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
by: Sun, Zexu, et al.
Published: (2023)
by: Sun, Zexu, et al.
Published: (2023)
Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs
by: Chen, Xiaoqing, et al.
Published: (2024)
by: Chen, Xiaoqing, et al.
Published: (2024)
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation
by: Zhang, Jiaxing, et al.
Published: (2024)
by: Zhang, Jiaxing, et al.
Published: (2024)
Generally-Occurring Model Change for Robust Counterfactual Explanations
by: Xu, Ao, et al.
Published: (2024)
by: Xu, Ao, et al.
Published: (2024)
TimeX++: Learning Time-Series Explanations with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)
by: Liu, Zichuan, et al.
Published: (2024)
Annealing Self-Distillation Rectification Improves Adversarial Training
by: Wu, Yu-Yu, et al.
Published: (2023)
by: Wu, Yu-Yu, et al.
Published: (2023)
Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
by: Lin, Fudong, et al.
Published: (2025)
by: Lin, Fudong, et al.
Published: (2025)
Causality-Aware Local Interpretable Model-Agnostic Explanations
by: Cinquini, Martina, et al.
Published: (2022)
by: Cinquini, Martina, et al.
Published: (2022)
Interpreting Language Reward Models via Contrastive Explanations
by: Jiang, Junqi, et al.
Published: (2024)
by: Jiang, Junqi, et al.
Published: (2024)
ADEdgeDrop: Adversarial Edge Dropping for Robust Graph Neural Networks
by: Chen, Zhaoliang, et al.
Published: (2024)
by: Chen, Zhaoliang, et al.
Published: (2024)
Adversarial Preference Learning for Robust LLM Alignment
by: Wang, Yuanfu, et al.
Published: (2025)
by: Wang, Yuanfu, et al.
Published: (2025)
Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing
by: Zhong, Xuyang, et al.
Published: (2025)
by: Zhong, Xuyang, et al.
Published: (2025)
Spectral Surgery: Training-Free Refinement of LoRA via Gradient-Guided Singular Value Reweighting
by: Tian, Zailong, et al.
Published: (2026)
by: Tian, Zailong, et al.
Published: (2026)
Explanation Space: A New Perspective into Time Series Interpretability
by: Rezaei, Shahbaz, et al.
Published: (2024)
by: Rezaei, Shahbaz, et al.
Published: (2024)
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
by: Zheng, Xu, et al.
Published: (2024)
by: Zheng, Xu, et al.
Published: (2024)
Training Free Guided Flow Matching with Optimal Control
by: Wang, Luran, et al.
Published: (2024)
by: Wang, Luran, et al.
Published: (2024)
TensorHyper-VQC: A Tensor-Train-Guided Hypernetwork for Robust and Scalable Variational Quantum Computing
by: Qi, Jun, et al.
Published: (2025)
by: Qi, Jun, et al.
Published: (2025)
FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning
by: Tang, Minxue, et al.
Published: (2024)
by: Tang, Minxue, et al.
Published: (2024)
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
by: Chen, Weixin, et al.
Published: (2025)
by: Chen, Weixin, et al.
Published: (2025)
Counterfactual Training: Teaching Models Plausible and Actionable Explanations
by: Altmeyer, Patrick, et al.
Published: (2026)
by: Altmeyer, Patrick, et al.
Published: (2026)
How Do Diffusion Models Improve Adversarial Robustness?
by: Yuezhang, Liu, et al.
Published: (2025)
by: Yuezhang, Liu, et al.
Published: (2025)
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
by: Zhang, Jiaxing, et al.
Published: (2023)
by: Zhang, Jiaxing, et al.
Published: (2023)
RainSeer: Fine-Grained Rainfall Reconstruction via Physics-Guided Modeling
by: Chen, Lin, et al.
Published: (2025)
by: Chen, Lin, et al.
Published: (2025)
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
by: Li, Zaitang, et al.
Published: (2023)
by: Li, Zaitang, et al.
Published: (2023)
Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change
by: Stępka, Ignacy, et al.
Published: (2024)
by: Stępka, Ignacy, et al.
Published: (2024)
Gradient Inversion Transcript: Leveraging Robust Generative Priors to Reconstruct Training Data from Gradient Leakage
by: Chen, Xinping, et al.
Published: (2025)
by: Chen, Xinping, et al.
Published: (2025)
Similar Items
-
From Attribution to Action: Jointly ALIGNing Predictions and Explanations
by: Hong, Dongsheng, et al.
Published: (2025) -
BAED: a New Paradigm for Few-shot Graph Learning with Explanation in the Loop
by: Chen, Chao, et al.
Published: (2026) -
Provable Robust Saliency-based Explanations
by: Chen, Chao, et al.
Published: (2022) -
A Survey on Memory-Efficient Transformer-Based Model Training in AI for Science
by: Tian, Kaiyuan, et al.
Published: (2025) -
Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
by: Zhang, Jiaxing, et al.
Published: (2025)