ExpProof : Operationalizing Explanations for Confidential Models with ZKPs

6 February 2025

Papers citing "ExpProof : Operationalizing Explanations for Confidential Models with ZKPs"

27 / 27 papers shown

Title
Auditing Local Explanations is Hard Robi Bhattacharjee U. V. Luxburg LRM MLAU FAtt 68 2 0 18 Jul 2024
zkLLM: Zero Knowledge Proofs for Large Language Models Haochen Sun Jason Li Hongyang Zhang ALM 66 26 0 24 Apr 2024
Trustless Audits without Revealing Data or Models Suppakit Waiwitlikhit Ion Stoica Yi Sun Tatsunori Hashimoto Daniel Kang MLAU 29 10 0 06 Apr 2024
FairProof : Confidential and Certifiable Fairness for Neural Networks Chhavi Yadav A. Chowdhury Dan Boneh Kamalika Chaudhuri MLAU 75 8 0 19 Feb 2024
Verifiable Fairness: Privacy-preserving Computation of Fairness for Machine Learning Systems Ehsan Toreini M. Mehrnezhad Aad van Moorsel 33 5 0 12 Sep 2023
Keeping Up with the Language Models: Robustness-Bias Interplay in NLI Data and Models Ioana Baldini Chhavi Yadav Payel Das Kush R. Varshney MLAU 50 3 0 22 May 2023
Scaling up Trustless DNN Inference with Zero-Knowledge Proofs Daniel Kang Tatsunori Hashimoto Ion Stoica Yi Sun LRM 21 41 0 17 Oct 2022
Active Fairness Auditing Tom Yan Chicheng Zhang FaML 114 25 0 16 Jun 2022
XAudit : A Theoretical Look at Auditing with Explanations Chhavi Yadav Michal Moshkovitz Kamalika Chaudhuri XAI FAtt MLAU 50 5 0 09 Jun 2022
Framework for Evaluating Faithfulness of Local Explanations S. Dasgupta Nave Frost Michal Moshkovitz FAtt 175 62 0 01 Feb 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts Sebastian Bordt Michèle Finck Eric Raidl U. V. Luxburg AILaw 77 78 0 25 Jan 2022
pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing Jiasi Weng Jian Weng Gui Tang Anjia Yang Ming Li Jia-Nan Liu 33 33 0 23 Jan 2022
Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System Timon Rückel Johannes Sedlmeir Peter Hofmann FedML 54 58 0 11 Nov 2021
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences Q. V. Liao R. Varshney 40 227 0 20 Oct 2021
Counterfactual Explanations Can Be Manipulated Dylan Slack Sophie Hilgard Himabindu Lakkaraju Sameer Singh 53 136 0 04 Jun 2021
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research Markus Langer Daniel Oster Timo Speith Holger Hermanns Lena Kästner Eva Schmidt Andreas Sesing Kevin Baum XAI 90 418 0 15 Feb 2021
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 50 172 0 08 Oct 2020
Looking Deeper into Tabular LIME Damien Garreau U. V. Luxburg FAtt LMTD 144 30 0 25 Aug 2020
Explaining the Explainer: A First Theoretical Analysis of LIME Damien Garreau U. V. Luxburg FAtt 32 175 0 10 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 265 42,038 0 03 Dec 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 59 813 0 06 Nov 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes Matt Jordan Justin Lewis A. Dimakis AAML 60 57 0 20 Mar 2019
Fairwashing: the risk of rationalization Ulrich Aïvodji Hiromi Arai O. Fortineau Sébastien Gambs Satoshi Hara Alain Tapp FaML 33 146 0 28 Jan 2019
Defining Locality for Surrogates in Post-hoc Interpretablity Thibault Laugel X. Renard Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki FAtt 76 80 0 19 Jun 2018
Inverse Classification for Comparison-based Interpretability in Machine Learning Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 108 100 0 22 Dec 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 81 2,332 0 01 Nov 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 587 16,828 0 16 Feb 2016