Chhavi Yadav

According to our database, Chhavi Yadav authored at least 12 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2025

Can We Infer Confidential Properties of Training Data from LLMs?

Pengrun Huang, Chhavi Yadav, Ruihan Wu, Kamalika Chaudhuri

CoRR, June, 2025

ExpProof : Operationalizing Explanations for Confidential Models with ZKPs.

Chhavi Yadav, Evan Laufer, Dan Boneh, Kamalika Chaudhuri

CoRR, February, 2025

The Mainstays of Trustworthy Machine Learning.

Chhavi Yadav

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

XAudit : A Learning-Theoretic Look at Auditing with Explanations.

Chhavi Yadav, Michal Moshkovitz, Kamalika Chaudhuri

Trans. Mach. Learn. Res., 2024

Evaluating Deep Unlearning in Large Language Models.

Ruihan Wu, Chhavi Yadav, Russ Salakhutdinov, Kamalika Chaudhuri

CoRR, 2024

Influence-based Attributions can be Manipulated.

Chhavi Yadav, Ruihan Wu, Kamalika Chaudhuri

CoRR, 2024

FairProof : Confidential and Certifiable Fairness for Neural Networks.

Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Keeping Up with the Language Models: Robustness-Bias Interplay in NLI Data and Models.

Ioana Baldini, Chhavi Yadav, Payel Das, Kush R. Varshney

CoRR, 2023

2022

A Learning-Theoretic Framework for Certified Auditing of Machine Learning Models.

Chhavi Yadav, Michal Moshkovitz, Kamalika Chaudhuri

CoRR, 2022

2021

Behavior of k-NN as an Instance-Based Explanation Method.

Chhavi Yadav, Kamalika Chaudhuri

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

2019

Cold Case: The Lost MNIST Digits.

Chhavi Yadav, Léon Bottou

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the design of convolutional neural networks for automatic detection of Alzheimer's disease.

Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian

Proceedings of the Machine Learning for Health Workshop, 2019