Cover Image

Correlation-Aware Feature Attribution Based Explainable AI

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sengupta, Poushali, Zhang, Yan, Eliassen, Frank, Maharjan, Sabita
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explainability of Complex AI Models with Correlation Impact Ratio
by: Sengupta, Poushali, et al.
Published: (2026)

Context Dependence and Reliability in Autoregressive Language Models
by: Sengupta, Poushali, et al.
Published: (2026)

Reliable Explanations or Random Noise? A Reliability Metric for XAI
by: Sengupta, Poushali, et al.
Published: (2026)

X-NegoBox: An Explainable Privacy-Budget Negotiation Framework for Secure Peer-to-Peer Energy Data Exchange
by: Sengupta, Poushali, et al.
Published: (2026)

Adaptive Quantum-Safe Cryptography for 6G Vehicular Networks via Context-Aware Optimization
by: Sengupta, Poushali, et al.
Published: (2026)

Privacy-Utility-Fairness: A Balanced Approach to Vehicular-Traffic Management System
by: Sengupta, Poushali, et al.
Published: (2025)

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability
by: Zhang, Shichang, et al.
Published: (2025)

Security, privacy, and agentic AI in a regulatory view: From definitions and distinctions to provisions and reflections
by: Zhang, Shiliang, et al.
Published: (2026)

AI and Open-data Driven Scalable Solar Power Profiling
by: Zhang, Shiliang, et al.
Published: (2026)

ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability
by: Zhu, Zhiyu, et al.
Published: (2025)

Explainable AI Through a Democratic Lens: DhondtXAI for D'Hondt-Projected Feature Attribution
by: Donmez, Turker Berk
Published: (2024)

Hybrid Attribution Priors for Explainable and Robust Model Training
by: Zhang, Zhuoran, et al.
Published: (2025)

A New Technique for AI Explainability using Feature Association Map
by: Ghosh, Sayantani, et al.
Published: (2026)

MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction
by: Zhang, Zizheng, et al.
Published: (2026)

Distribution-Based Feature Attribution for Explaining the Predictions of Any Classifier
by: Li, Xinpeng, et al.
Published: (2025)

Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
by: Ng, Woon Yee, et al.
Published: (2025)

Sparse, Efficient and Explainable Data Attribution with DualXDA
by: Yolcu, Galip Ümit, et al.
Published: (2024)

Impossibility Theorems for Feature Attribution
by: Bilodeau, Blair, et al.
Published: (2022)

A Backdoor-based Explainable AI Benchmark for High Fidelity Evaluation of Attributions
by: Yang, Peiyu, et al.
Published: (2024)

Probabilistic Stability Guarantees for Feature Attributions
by: Jin, Helen, et al.
Published: (2025)

Probe-Based Data Attribution: Discovering and Mitigating Undesirable Behaviors in LLM Post-Training
by: Xiao, Frank, et al.
Published: (2026)

Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems
by: Yakubu, Paul Badu, et al.
Published: (2024)

A Dual-Perspective Approach to Evaluating Feature Attribution Methods
by: Li, Yawei, et al.
Published: (2023)

On the Properties of Feature Attribution for Supervised Contrastive Learning
by: Arrighi, Leonardo, et al.
Published: (2026)

Integrated Gradient Correlation: a Dataset-wise Attribution Method
by: Lelièvre, Pierre, et al.
Published: (2024)

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends
by: Zhang, Xin, et al.
Published: (2024)

Explainable AI needs formalization
by: Haufe, Stefan, et al.
Published: (2024)

Interaction-Aware Influence Functions for Group Attribution
by: Heo, Jaeseung, et al.
Published: (2026)

Towards Trustworthy Keylogger detection: A Comprehensive Analysis of Ensemble Techniques and Feature Selections through Explainable AI
by: Mahmud, Monirul Islam
Published: (2025)

Towards User-Focused Research in Training Data Attribution for Human-Centered Explainable AI
by: Nguyen, Elisa, et al.
Published: (2024)

Bridging Explainability and Embeddings: BEE Aware of Spuriousness
by: Păduraru, Cristian Daniel, et al.
Published: (2024)

Multi-Task Semantic Communication With Graph Attention-Based Feature Correlation Extraction
by: Yu, Xi, et al.
Published: (2025)

TangledFeatures: Robust Feature Selection in Highly Correlated Spaces
by: Sunny, Allen Daniel
Published: (2025)

Rethinking Explainability in the Era of Multimodal AI
by: Agarwal, Chirag
Published: (2025)

Explainable AI For Early Detection Of Sepsis
by: Thakur, Atharva, et al.
Published: (2025)

Verifying Machine Unlearning with Explainable AI
by: Vidal, Àlex Pujol, et al.
Published: (2024)

A Polynomial-Time Axiomatic Alternative to SHAP for Feature Attribution
by: Hiraki, Kazuhiro, et al.
Published: (2026)

Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence
by: Mikriukov, Georgii, et al.
Published: (2026)

Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution
by: Hinterleitner, Alexander, et al.
Published: (2024)

Tabular Data Contrastive Learning via Class-Conditioned and Feature-Correlation Based Augmentation
by: Cui, Wei, et al.
Published: (2024)