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Workshop
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Generating Global Factual and Counterfactual Explainer for Molecule under Domain Constraints
Danqing Wang · Antonis Antoniades · Ambuj Singh · Lei Li
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Workshop
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Accurate, Explainable, and Private Models: Providing Recourse While Minimizing Training Data Leakage
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Workshop
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Why do universal adversarial attacks work on large language models?: Geometry might be the answer
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Workshop
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Scoring Black-Box Models for Adversarial Robustness
Jian Vora · Pranay Reddy Samala
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Workshop
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Adversarial Attacks and Defenses in Explainable Artificial Intelligence: A Survey
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Workshop
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Don't trust your eyes: on the (un)reliability of feature visualizations
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Workshop
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State trajectory abstraction and visualization method for explainability in reinforcement learning
Yoshiki Takagi · roderick tabalba · Jason Leigh
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Workshop
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Fri 14:10
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Invited talk: Rajesh Ranganath - Have we learned to explain?
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Workshop
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Sat 13:30
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Himabindu Lakkaraju - Regulating Explainable AI: Technical Challenges and Opportunities
Hima Lakkaraju
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Workshop
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Adversarial Attacks and Defenses in Explainable Artificial Intelligence: A Survey
Hubert Baniecki · Przemyslaw Biecek
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Workshop
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Fri 14:10
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Explaining Graph Neural Networks Using Interpretable Local Surrogates
Farzaneh Heidari · Guillaume Rabusseau · Perouz Taslakian
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Workshop
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Toward Practical Automatic Speech Recognition and Post-Processing: a Call for Explainable Error Benchmark Guideline
Seonmin Koo · Chanjun Park · Jinsung Kim · Jaehyung Seo · Sugyeong Eo · Hyeonseok Moon · HEUISEOK LIM
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