Cover Image

Towards a Unified Framework for Evaluating Explanations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pinto, Juan D., Paquette, Luc
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A constraints-based approach to fully interpretable neural networks for detecting learner behaviors
by: Pinto, Juan D., et al.
Published: (2025)

Deep Learning for Educational Data Science
by: Pinto, Juan D., et al.
Published: (2024)

OpenXAI: Towards a Transparent Evaluation of Model Explanations
by: Agarwal, Chirag, et al.
Published: (2022)

Explanations are a Means to an End: Decision Theoretic Explanation Evaluation
by: Guo, Ziyang, et al.
Published: (2025)

DeepFaith: A Domain-Free and Model-Agnostic Unified Framework for Highly Faithful Explanations
by: Guo, Yuhan, et al.
Published: (2025)

Towards a Unified Framework of Clustering-based Anomaly Detection
by: Fang, Zeyu, et al.
Published: (2024)

A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability
by: Fatemi, Pouria, et al.
Published: (2025)

Unifying Attribution-Based Explanations Using Functional Decomposition
by: Gevaert, Arne, et al.
Published: (2024)

Unifying Post-hoc Explanations of Knowledge Graph Completions
by: Lonardi, Alessandro, et al.
Published: (2025)

Towards Understanding the Influence of Training Samples on Explanations
by: Artelt, André, et al.
Published: (2024)

Toward a Unified Geometry Understanding: Riemannian Diffusion Framework for Graph Generation and Prediction
by: Gao, Yisen, et al.
Published: (2025)

Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery
by: Yue, Linan, et al.
Published: (2024)

Towards Piece-by-Piece Explanations for Chess Positions with SHAP
by: Spinnato, Francesco
Published: (2025)

Towards Verified and Targeted Explanations through Formal Methods
by: Wang, Hanchen David, et al.
Published: (2026)

Evaluating the Ability of Explanations to Disambiguate Models in a Rashomon Set
by: Rawal, Kaivalya, et al.
Published: (2026)

Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI
by: Dembinsky, David, et al.
Published: (2025)

CohEx: A Generalized Framework for Cohort Explanation
by: Meng, Fanyu, et al.
Published: (2024)

Procrustean Bed for AI-Driven Retrosynthesis: A Unified Framework for Reproducible Evaluation
by: Morgunov, Anton, et al.
Published: (2025)

Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning
by: Chen, Yanda, et al.
Published: (2024)

A Unifying Framework for Learning Argumentation Semantics
by: Mileva, Zlatina, et al.
Published: (2023)

xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods
by: Seth, Pratinav, et al.
Published: (2025)

Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels
by: Furman, Oleksii, et al.
Published: (2024)

Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
by: Sheng, Zhecheng, et al.
Published: (2025)

TREX: Trajectory Explanations for Multi-Objective Reinforcement Learning
by: Rajapakse, Dilina, et al.
Published: (2026)

Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependency, Asynchrony, and Missingness
by: Jang, Jinkwan, et al.
Published: (2025)

Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
by: Schnake, Thomas, et al.
Published: (2024)

RealAC: A Domain-Agnostic Framework for Realistic and Actionable Counterfactual Explanations
by: Arefeen, Asiful, et al.
Published: (2025)

Evaluating LLM-Based Process Explanations under Progressive Behavioral-Input Reduction
by: van Oerle, P., et al.
Published: (2025)

A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges
by: Prado-Romero, Mario Alfonso, et al.
Published: (2022)

UniSD: Towards a Unified Self-Distillation Framework for Large Language Models
by: Jin, Yiqiao, et al.
Published: (2026)

Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
by: Zhang, Jiaxing, et al.
Published: (2025)

A Unified Framework for Locality in Scalable MARL
by: Chakraborty, Sourav, et al.
Published: (2026)

CoSy: Evaluating Textual Explanations of Neurons
by: Kopf, Laura, et al.
Published: (2024)

Delivering Inflated Explanations
by: Izza, Yacine, et al.
Published: (2023)

A Novel Multimodal RUL Framework for Remaining Useful Life Estimation with Layer-wise Explanations
by: Razzaq, Waleed, et al.
Published: (2025)

Comparative Explanations: Explanation Guided Decision Making for Human-in-the-Loop Preference Selection
by: Chakraborty, Tanmay, et al.
Published: (2025)

AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language Models
by: Cheng, Jiale, et al.
Published: (2024)

BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
by: Lidayan, Aly, et al.
Published: (2024)

Towards Intelligent Energy Security: A Unified Spatio-Temporal and Graph Learning Framework for Scalable Electricity Theft Detection in Smart Grids
by: Olowookere, AbdulQoyum A., et al.
Published: (2026)

UGMAE: A Unified Framework for Graph Masked Autoencoders
by: Tian, Yijun, et al.
Published: (2024)