Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models
- Myles Foley
- Ambrish Rawat
- et al.
- 2023
- ACL 2023
Ambrish Rawat is a Research Scientist in the AI Security & Privacy team at IBM. His research interests are at the cross-sections of security, privacy and Artificial Intelligence (AI). Most recently, he has worked on Privacy Enhancing Technologies (PETs) like Federated Learning and Differential Privacy. He is passionate about building trustworthy AI systems with security and privacy guarantees within the regulatory demands of GDPR as well as EU AI and Digital Acts.
He holds a Master of Philosophy in Machine Learning and Machine Intelligence from the University of Cambridge, UK, and a Master of Technology in Mathematics and Computing from the Indian Institute of Technology, Delhi (IIT Delhi). He joined IBM in 2016 and has since been leading and contributing to numerous efforts in AI and ML at the Dublin Research Lab.
His work has been published at top AI conferences and he's an active contributor to open source software projects. He have been recognised as Master Inventor at IBM for his contributions to IBM patent portfolio and has also received Research Division Award and several Outstanding Technical Accomplishment Awards for the contributions to the vast array of cutting-edge research at IBM.