ICML Poster "model interpretability" Papers
10 papers found
Attribution-based Explanations that Provide Recourse Cannot be Robust
Hidde Fokkema, Rianne de Heide, Tim van Erven
ICML 2024posterarXiv:2205.15834
Explaining Graph Neural Networks via Structure-aware Interaction Index
Ngoc Bui, Trung Hieu Nguyen, Viet Anh Nguyen et al.
ICML 2024posterarXiv:2405.14352
Exploring the LLM Journey from Cognition to Expression with Linear Representations
Yuzi Yan, Jialian Li, YipinZhang et al.
ICML 2024posterarXiv:2405.16964
Improving Neural Additive Models with Bayesian Principles
Kouroche Bouchiat, Alexander Immer, Hugo Yèche et al.
ICML 2024posterarXiv:2305.16905
Iterative Search Attribution for Deep Neural Networks
Zhiyu Zhu, Huaming Chen, Xinyi Wang et al.
ICML 2024poster
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki et al.
ICML 2024poster
On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
Yi Cai, Gerhard Wunder
ICML 2024posterarXiv:2308.09381
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh
ICML 2024posterarXiv:2406.01757
Position: Stop Making Unscientific AGI Performance Claims
Patrick Altmeyer, Andrew Demetriou, Antony Bartlett et al.
ICML 2024posterarXiv:2402.03962
Provably Better Explanations with Optimized Aggregation of Feature Attributions
Thomas Decker, Ananta Bhattarai, Jindong Gu et al.
ICML 2024posterarXiv:2406.05090