Yadav, Chhavi

10 publications

NeurIPS 2025 Can We Infer Confidential Properties of Training Data from LLMs? Pengrun Huang, Chhavi Yadav, Kamalika Chaudhuri, Ruihan Wu

ICML 2025 ExpProof : Operationalizing Explanations for Confidential Models with ZKPs Chhavi Yadav, Evan Laufer, Dan Boneh, Kamalika Chaudhuri

ICLRW 2025 ExpProof : Operationalizing Explanations for Confidential Models with ZKPs Chhavi Yadav, Evan Laufer, Dan Boneh, Kamalika Chaudhuri

AAAI 2025 The Mainstays of Trustworthy Machine Learning Chhavi Yadav

ICML 2024 FairProof : Confidential and Certifiable Fairness for Neural Networks Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri

ICLRW 2024 FairProof : Confidential and Certifiable Fairness for Neural Networks Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri

NeurIPSW 2024 FairProof : Confidential and Certifiable Fairness for Neural Networks Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri

NeurIPSW 2024 Influence-Based Attributions Can Be Manipulated Chhavi Yadav, Ruihan Wu, Kamalika Chaudhuri

TMLR 2024 XAudit : A Learning-Theoretic Look at Auditing with Explanations Chhavi Yadav, Michal Moshkovitz, Kamalika Chaudhuri

NeurIPS 2019 Cold Case: The Lost MNIST Digits Chhavi Yadav, Leon Bottou