Cover Image

Exploring the Relationship Between Feature Attribution Methods and Model Performance

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Silva, Priscylla, Silva, Claudio T., Nonato, Luis Gustavo
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Exploring Urban Factors with Autoencoders: Relationship Between Static and Dynamic Features
by: Pocco, Ximena, et al.
Published: (2025)

Assessing Large Language Models for Automated Feedback Generation in Learning Programming Problem Solving
by: Silva, Priscylla, et al.
Published: (2025)

T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients
by: Ortigossa, Evandro S., et al.
Published: (2024)

TiVy: Time Series Visual Summary for Scalable Visualization
by: Chan, Gromit Yeuk-Yin, et al.
Published: (2025)

The Attribution Contract: Feature Attribution for Generative Language Models
by: Nguyen, Giang
Published: (2026)

On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders
by: Simon, Elana, et al.
Published: (2026)

Topo-GS: Continuous Volumetric Embedding of High-Dimensional Data via Topological Gaussian Splatting
by: Gois, João Paulo, et al.
Published: (2026)

Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability
by: Lee, Ivan, et al.
Published: (2023)

TopoMap++: A faster and more space efficient technique to compute projections with topological guarantees
by: Guardieiro, Vitoria, et al.
Published: (2024)

Model Guidance via Robust Feature Attribution
by: Ghitu, Mihnea, et al.
Published: (2025)

Evaluating Feature Attribution Methods in the Image Domain
by: Gevaert, Arne, et al.
Published: (2022)

Exploring the Relationships Between Physiological Signals During Automated Fatigue Detection
by: Kakhi, Kourosh, et al.
Published: (2025)

When is the Computation of a Feature Attribution Method Tractable?
by: Barceló, P., et al.
Published: (2025)

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

MOUNTAINEER: Topology-Driven Visual Analytics for Comparing Local Explanations
by: Solunke, Parikshit, et al.
Published: (2024)

AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments
by: Zhang, Yang, et al.
Published: (2023)

ReAGent: A Model-agnostic Feature Attribution Method for Generative Language Models
by: Zhao, Zhixue, et al.
Published: (2024)

Systematic Evaluation of Attribution Methods: Eliminating Threshold Bias and Revealing Method-Dependent Performance Patterns
by: Aksoy, Serra
Published: (2025)

Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance
by: Aliakbarisani, Roya, et al.
Published: (2024)

Disentangling Interactions and Dependencies in Feature Attribution
by: König, Gunnar, et al.
Published: (2024)

Feature Attribution from First Principles
by: Taimeskhanov, Magamed, et al.
Published: (2025)

Training Feature Attribution for Vision Models
by: Bacha, Aziz, et al.
Published: (2025)

Energy-Based Model for Accurate Estimation of Shapley Values in Feature Attribution
by: Lu, Cheng, et al.
Published: (2024)

Model Monitoring in the Absence of Labeled Data via Feature Attributions Distributions
by: Mougan, Carlos
Published: (2025)

Invariant Features in Language Models: Geometric Characterization and Model Attribution
by: Dasgupta, Agnibh, et al.
Published: (2026)

Explaining Concept Shift with Interpretable Feature Attribution
by: Lyu, Ruiqi, et al.
Published: (2025)

Boundary-Aware Uncertainty for Feature Attribution Explainers
by: Hill, Davin, et al.
Published: (2022)

Missingness Bias Calibration in Feature Attribution Explanations
by: Sridhar, Shailesh, et al.
Published: (2026)

Backward Compatibility in Attributive Explanation and Enhanced Model Training Method
by: Matsuno, Ryuta
Published: (2024)

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

Model-Based Counterfactual Explanations Incorporating Feature Space Attributes for Tabular Data
by: Sumiya, Yuta, et al.
Published: (2024)

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

The Relationship Between Reasoning and Performance in Large Language Models -- o3 (mini) Thinks Harder, Not Longer
by: Ballon, Marthe, et al.
Published: (2025)

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

Toward Understanding the Disagreement Problem in Neural Network Feature Attribution
by: Koenen, Niklas, et al.
Published: (2024)

Enhancing Visual Feature Attribution via Weighted Integrated Gradients
by: Tuan, Kien Tran Duc, et al.
Published: (2025)

Consistency of Feature Attribution in Deep Learning Architectures for Multi-Omics
by: Claborne, Daniel, et al.
Published: (2025)

Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set
by: Laberge, Gabriel, et al.
Published: (2021)

Rethinking Robustness: A New Approach to Evaluating Feature Attribution Methods
by: Kiourti, Panagiota, et al.
Published: (2025)

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