Cover Image

Model Explanations via the Axiomatic Causal Lens

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Biradar, Gagan, Viswanathan, Vignesh, Zick, Yair
Format:	Preprint
Published:	2021
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Simple Steps to Success: A Method for Step-Based Counterfactual Explanations
by: Hamer, Jenny, et al.
Published: (2023)

Stable Matching under Matroid Rank Valuations
by: Eden, Alon, et al.
Published: (2025)

On the Hardness of Fair Allocation under Ternary Valuations
by: Fitzsimmons, Zack, et al.
Published: (2024)

An Axiomatic Approach to Model-Agnostic Concept Explanations
by: Feng, Zhili, et al.
Published: (2024)

RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
by: Chowdhury, Tanya, et al.
Published: (2024)

Hedonic Neurons: A Mechanistic Mapping of Latent Coalitions in Transformer MLPs
by: Chowdhury, Tanya, et al.
Published: (2025)

Axiomatic Foundations of Counterfactual Explanations
by: Amgoud, Leila, et al.
Published: (2026)

Fair and Welfare-Efficient Constrained Multi-matchings under Uncertainty
by: Lobo, Elita, et al.
Published: (2024)

Percentile Criterion Optimization in Offline Reinforcement Learning
by: Lobo, Elita A., et al.
Published: (2024)

Graph Neural Network Causal Explanation via Neural Causal Models
by: Behnam, Arman, et al.
Published: (2024)

HistoLens: An Interactive XAI Toolkit for Verifying and Mitigating Flaws in Vision-Language Models for Histopathology
by: Vissapragada, Sandeep, et al.
Published: (2025)

Teaching Transformers Causal Reasoning through Axiomatic Training
by: Vashishtha, Aniket, et al.
Published: (2024)

Axiomatic Explainer Globalness via Optimal Transport
by: Hill, Davin, et al.
Published: (2024)

Identifiable Latent Polynomial Causal Models Through the Lens of Change
by: Liu, Yuhang, et al.
Published: (2023)

Linking Model Intervention to Causal Interpretation in Model Explanation
by: Cheng, Debo, et al.
Published: (2024)

Heterogeneous Multi-Agent Bandits with Parsimonious Hints
by: Mirfakhar, Amirmahdi, et al.
Published: (2025)

Attention Augmented GNN RNN-Attention Models for Advanced Cybersecurity Intrusion Detection
by: Biradar, Jayant, et al.
Published: (2025)

Attention Deficits in Language Models: Causal Explanations for Procedural Hallucinations
by: Karim, Ahmed, et al.
Published: (2026)

Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations
by: Ben-Yair, Ido, et al.
Published: (2021)

Causality-Aware Local Interpretable Model-Agnostic Explanations
by: Cinquini, Martina, et al.
Published: (2022)

Towards AI Transparency and Accountability: A Global Framework for Exchanging Information on AI Systems
by: Buckley, Warren, et al.
Published: (2023)

Causal Graph Profiling via Structural Divergence for Robust Anomaly Detection in Cyber-Physical Systems
by: Malarkkan, Arun Vignesh, et al.
Published: (2025)

Wasserstein Distributionally Robust Optimization Through the Lens of Structural Causal Models and Individual Fairness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

Validating Mechanistic Interpretations: An Axiomatic Approach
by: Palumbo, Nils, et al.
Published: (2024)

A Model of Causal Explanation on Neural Networks for Tabular Data
by: Isozaki, Takashi, et al.
Published: (2025)

Towards Understanding Extrapolation: a Causal Lens
by: Kong, Lingjing, et al.
Published: (2025)

Explaining Risks: Axiomatic Risk Attributions for Financial Models
by: Chen, Dangxing
Published: (2025)

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
by: Chen, Xuexin, et al.
Published: (2024)

An Axiomatic Definition of Hierarchical Clustering
by: Arias-Castro, Ery, et al.
Published: (2024)

Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
by: Parafita, Álvaro, et al.
Published: (2025)

Causal Explanation of Concept Drift -- A Truly Actionable Approach
by: Komnick, David, et al.
Published: (2025)

New User Event Prediction Through the Lens of Causal Inference
by: Yuchi, Henry Shaowu, et al.
Published: (2024)

Deep Backtracking Counterfactuals for Causally Compliant Explanations
by: Kladny, Klaus-Rudolf, et al.
Published: (2023)

An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm
by: Pacheco, Armando J. Cabrera, et al.
Published: (2024)

Axiomatization of Gradient Smoothing in Neural Networks
by: Zhou, Linjiang, et al.
Published: (2024)

Counterfactual Explanations of Black-box Machine Learning Models using Causal Discovery with Applications to Credit Rating
by: Takahashi, Daisuke, et al.
Published: (2024)

Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learning
by: Malarkkan, Arun Vignesh, et al.
Published: (2026)

Rethinking Bivariate Causal Discovery Through the Lens of Exchangeability
by: Brogueira, Tiago, et al.
Published: (2025)

A Causal Lens for Learning Long-term Fair Policies
by: Lear, Jacob, et al.
Published: (2025)

Towards Complete Causal Explanation with Expert Knowledge
by: Venkateswaran, Aparajithan, et al.
Published: (2024)