Cover Image

What Makes a Good Explanation?: A Harmonized View of Properties of Explanations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Zixi, Subhash, Varshini, Havasi, Marton, Pan, Weiwei, Doshi-Velez, Finale
Format:	Preprint
Published:	2022
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Guarantee Regions for Local Explanations
by: Havasi, Marton, et al.
Published: (2024)

Diverse Concept Proposals for Concept Bottleneck Models
by: Brown, Katrina, et al.
Published: (2024)

Transparent Trade-offs between Properties of Explanations
by: Tadesse, Hiwot Belay, et al.
Published: (2024)

Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders
by: Yacoby, Yaniv, et al.
Published: (2024)

A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning
by: Nofshin, Eura, et al.
Published: (2024)

Inverse Reinforcement Learning with Multiple Planning Horizons
by: Yao, Jiayu, et al.
Published: (2024)

Strategically Linked Decisions in Long-Term Planning and Reinforcement Learning
by: Hüyük, Alihan, et al.
Published: (2025)

Semi-parametric Expert Bayesian Network Learning with Gaussian Processes and Horseshoe Priors
by: Weng, Yidou, et al.
Published: (2024)

Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks
by: Nofshin, Eura, et al.
Published: (2024)

Towards Integrating Personal Knowledge into Test-Time Predictions
by: Lage, Isaac, et al.
Published: (2024)

On the Effective Horizon of Inverse Reinforcement Learning
by: Xu, Yiqing, et al.
Published: (2023)

Connecting Federated ADMM to Bayes
by: Swaroop, Siddharth, et al.
Published: (2025)

Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
by: Benac, Leo, et al.
Published: (2026)

Decision-Point Guided Safe Policy Improvement
by: Sharma, Abhishek, et al.
Published: (2024)

Decision-Focused Model-based Reinforcement Learning for Reward Transfer
by: Sharma, Abhishek, et al.
Published: (2023)

Bayesian Inverse Transition Learning: Learning Dynamics From Near-Optimal Trajectories
by: Benac, Leo, et al.
Published: (2024)

A Benchmark for Multi-Party Negotiation Games from Real Negotiation Data
by: Benac, Leo, et al.
Published: (2026)

Federated ADMM from Bayesian Duality
by: Möllenhoff, Thomas, et al.
Published: (2025)

Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills
by: Buçinca, Zana, et al.
Published: (2024)

Edit Flows: Flow Matching with Edit Operations
by: Havasi, Marton, et al.
Published: (2025)

View-based Explanations for Graph Neural Networks
by: Chen, Tingyang, et al.
Published: (2024)

Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models
by: Zhang, Ze Yu, et al.
Published: (2024)

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

On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
by: Cai, Yi, et al.
Published: (2023)

Understanding and Mitigating Tokenization Bias in Language Models
by: Phan, Buu, et al.
Published: (2024)

Database Views as Explanations for Relational Deep Learning
by: Rissaki, Agapi, et al.
Published: (2025)

"Faithful to What?" On the Limits of Fidelity-Based Explanations
by: Eshbaugh, Jackson
Published: (2025)

Sufficient and Necessary Explanations (and What Lies in Between)
by: Bharti, Beepul, et al.
Published: (2024)

Inductive Models for Artificial Intelligence Systems are Insufficient without Good Explanations
by: Habaraduwa, Udesh
Published: (2024)

Good Teachers Explain: Explanation-Enhanced Knowledge Distillation
by: Parchami-Araghi, Amin, et al.
Published: (2024)

Pruning the Path to Optimal Care: Identifying Systematically Suboptimal Medical Decision-Making with Inverse Reinforcement Learning
by: Bovenzi, Inko, et al.
Published: (2024)

What Makes a Good Diffusion Planner for Decision Making?
by: Lu, Haofei, et al.
Published: (2025)

Non-Stationary Latent Auto-Regressive Bandits
by: Trella, Anna L., et al.
Published: (2024)

AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties
by: Ji, Xiayan, et al.
Published: (2024)

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

Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles
by: Phan, Buu, et al.
Published: (2024)

What-If Explanations Over Time: Counterfactuals for Time Series Classification
by: Schlegel, Udo, et al.
Published: (2026)

Beware of "Explanations" of AI
by: Martens, David, et al.
Published: (2025)

SEEN: Sharpening Explanations for Graph Neural Networks using Explanations from Neighborhoods
by: Cho, Hyeoncheol, et al.
Published: (2021)

Yantra AI -- An intelligence platform which interacts with manufacturing operations
by: Krishnamurthy, Varshini
Published: (2025)