SHAP-based Explanations are Sensitive to Feature Representation
Fuente:
arXiv
Guardado en:
| Autores principales: | Hwang, Hyunseung, Bell, Andrew, Fonseca, Joao, Pliatsika, Venetia, Stoyanovich, Julia, Whang, Steven Euijong |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Explanation Multiplicity in SHAP: Characterization and Assessment
por: Hwang, Hyunseung, et al.
Publicado: (2026)
por: Hwang, Hyunseung, et al.
Publicado: (2026)
ShaRP: Explaining Rankings and Preferences with Shapley Values
por: Pliatsika, Venetia, et al.
Publicado: (2024)
por: Pliatsika, Venetia, et al.
Publicado: (2024)
Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs
por: Fonseca, Joao, et al.
Publicado: (2025)
por: Fonseca, Joao, et al.
Publicado: (2025)
ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations
por: Fonseca, Joao, et al.
Publicado: (2026)
por: Fonseca, Joao, et al.
Publicado: (2026)
GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning
por: Kim, Minsu, et al.
Publicado: (2025)
por: Kim, Minsu, et al.
Publicado: (2025)
Fair Class-Incremental Learning using Sample Weighting
por: Park, Jaeyoung, et al.
Publicado: (2024)
por: Park, Jaeyoung, et al.
Publicado: (2024)
PFGuard: A Generative Framework with Privacy and Fairness Safeguards
por: Kim, Soyeon, et al.
Publicado: (2024)
por: Kim, Soyeon, et al.
Publicado: (2024)
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
por: Lee, Jaejun, et al.
Publicado: (2024)
por: Lee, Jaejun, et al.
Publicado: (2024)
MIDAS: Misalignment-based Data Augmentation Strategy for Imbalanced Multimodal Learning
por: Hwang, Seong-Hyeon, et al.
Publicado: (2025)
por: Hwang, Seong-Hyeon, et al.
Publicado: (2025)
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
por: Oh, Jio, et al.
Publicado: (2024)
por: Oh, Jio, et al.
Publicado: (2024)
From SHAP Scores to Feature Importance Scores
por: Letoffe, Olivier, et al.
Publicado: (2024)
por: Letoffe, Olivier, et al.
Publicado: (2024)
On the Tractability of SHAP Explanations under Markovian Distributions
por: Marzouk, Reda, et al.
Publicado: (2024)
por: Marzouk, Reda, et al.
Publicado: (2024)
Towards Piece-by-Piece Explanations for Chess Positions with SHAP
por: Spinnato, Francesco
Publicado: (2025)
por: Spinnato, Francesco
Publicado: (2025)
T-CIL: Temperature Scaling using Adversarial Perturbation for Calibration in Class-Incremental Learning
por: Hwang, Seong-Hyeon, et al.
Publicado: (2025)
por: Hwang, Seong-Hyeon, et al.
Publicado: (2025)
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasks
por: Hwang, Seong-Hyeon, et al.
Publicado: (2024)
por: Hwang, Seong-Hyeon, et al.
Publicado: (2024)
ContextualSHAP : Enhancing SHAP Explanations Through Contextual Language Generation
por: Dwiyanti, Latifa, et al.
Publicado: (2025)
por: Dwiyanti, Latifa, et al.
Publicado: (2025)
Towards trustable SHAP scores
por: Letoffe, Olivier, et al.
Publicado: (2024)
por: Letoffe, Olivier, et al.
Publicado: (2024)
VirnyFlow: A Design Space for Responsible Model Development
por: Herasymuk, Denys, et al.
Publicado: (2025)
por: Herasymuk, Denys, et al.
Publicado: (2025)
Making Transparency Advocates: An Educational Approach Towards Better Algorithmic Transparency in Practice
por: Bell, Andrew, et al.
Publicado: (2024)
por: Bell, Andrew, et al.
Publicado: (2024)
Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers
por: Chung, Chanyoung, et al.
Publicado: (2023)
por: Chung, Chanyoung, et al.
Publicado: (2023)
CAFO: Feature-Centric Explanation on Time Series Classification
por: Kim, Jaeho, et al.
Publicado: (2024)
por: Kim, Jaeho, et al.
Publicado: (2024)
Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity Recognition
por: Tempel, Felix, et al.
Publicado: (2024)
por: Tempel, Felix, et al.
Publicado: (2024)
Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion
por: Lee, Jaejun, et al.
Publicado: (2026)
por: Lee, Jaejun, et al.
Publicado: (2026)
A Polynomial-Time Axiomatic Alternative to SHAP for Feature Attribution
por: Hiraki, Kazuhiro, et al.
Publicado: (2026)
por: Hiraki, Kazuhiro, et al.
Publicado: (2026)
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
por: Roh, Yuji, et al.
Publicado: (2024)
por: Roh, Yuji, et al.
Publicado: (2024)
DeFrame: Debiasing Large Language Models Against Framing Effects
por: Lim, Kahee, et al.
Publicado: (2026)
por: Lim, Kahee, et al.
Publicado: (2026)
SHAP scores fail pervasively even when Lipschitz succeeds
por: Letoffe, Olivier, et al.
Publicado: (2024)
por: Letoffe, Olivier, et al.
Publicado: (2024)
Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity
por: Bell, Andrew, et al.
Publicado: (2024)
por: Bell, Andrew, et al.
Publicado: (2024)
PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression
por: Fumagalli, Fabian, et al.
Publicado: (2026)
por: Fumagalli, Fabian, et al.
Publicado: (2026)
Interaction Tensor SHAP
por: Hasegawa, Hiroki, et al.
Publicado: (2025)
por: Hasegawa, Hiroki, et al.
Publicado: (2025)
Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
por: Ng, Woon Yee, et al.
Publicado: (2025)
por: Ng, Woon Yee, et al.
Publicado: (2025)
An Epistemic and Aleatoric Decomposition of Arbitrariness to Constrain the Set of Good Models
por: Khan, Falaah Arif, et al.
Publicado: (2023)
por: Khan, Falaah Arif, et al.
Publicado: (2023)
A New Paradigm for Counterfactual Reasoning in Fairness and Recourse
por: Bynum, Lucius E. J., et al.
Publicado: (2024)
por: Bynum, Lucius E. J., et al.
Publicado: (2024)
Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation
por: Khan, Falaah Arif, et al.
Publicado: (2024)
por: Khan, Falaah Arif, et al.
Publicado: (2024)
How to safely discard features based on aggregate SHAP values
por: Bhattacharjee, Robi, et al.
Publicado: (2025)
por: Bhattacharjee, Robi, et al.
Publicado: (2025)
CS-SHAP: Extending SHAP to Cyclic-Spectral Domain for Better Interpretability of Intelligent Fault Diagnosis
por: Chen, Qian, et al.
Publicado: (2025)
por: Chen, Qian, et al.
Publicado: (2025)
Do's and Don'ts: Learning Desirable Skills with Instruction Videos
por: Kim, Hyunseung, et al.
Publicado: (2024)
por: Kim, Hyunseung, et al.
Publicado: (2024)
FORCE: Feature-Oriented Representation with Clustering and Explanation
por: Mukherjee, Rishav, et al.
Publicado: (2025)
por: Mukherjee, Rishav, et al.
Publicado: (2025)
CNN-TFT explained by SHAP with multi-head attention weights for time series forecasting
por: Stefenon, Stefano F., et al.
Publicado: (2025)
por: Stefenon, Stefano F., et al.
Publicado: (2025)
Can Global XAI Methods Reveal Injected Bias in LLMs? SHAP vs Rule Extraction vs RuleSHAP
por: Sovrano, Francesco
Publicado: (2025)
por: Sovrano, Francesco
Publicado: (2025)
Ejemplares similares
-
Explanation Multiplicity in SHAP: Characterization and Assessment
por: Hwang, Hyunseung, et al.
Publicado: (2026) -
ShaRP: Explaining Rankings and Preferences with Shapley Values
por: Pliatsika, Venetia, et al.
Publicado: (2024) -
Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs
por: Fonseca, Joao, et al.
Publicado: (2025) -
ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations
por: Fonseca, Joao, et al.
Publicado: (2026) -
GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning
por: Kim, Minsu, et al.
Publicado: (2025)