163 citations · 1.4k across the 139 of their papers we have counts for
15 papers · 1 filter
RESTOR: Knowledge Recovery in Machine Unlearning
Keivan Rezaei, Khyathi Chandu, Soheil Feizi +3
Large language models trained on web-scale corpora can memorize undesirable data containing misinformation, copyrighted material, or private or sensitive information. Recently, sev…
Unearthing Skill-Level Insights for Understanding Trade-Offs of Foundation Models
Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran +6
With models getting stronger, evaluations have grown more complex, testing multiple skills in one benchmark and even in the same instance at once. However, skill-wise performance i…
Securing the Future of GenAI: Policy and Technology
Mihai Christodorescu, Ryan Craven, Soheil Feizi +11
The rise of Generative AI (GenAI) brings about transformative potential across sectors, but its dual-use nature also amplifies risks. Governments globally are grappling with the ch…
DREW : Towards Robust Data Provenance by Leveraging Error-Controlled Watermarking
Mehrdad Saberi, Vinu Sankar Sadasivan, Arman Zarei +2
Identifying the origin of data is crucial for data provenance, with applications including data ownership protection, media forensics, and detecting AI-generated content. A standar…
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning
Soumya Suvra Ghosal, Samyadeep Basu, Soheil Feizi +1
Image-text contrastive models such as CLIP learn transferable and robust representations for zero-shot transfer to a variety of downstream tasks. However, to obtain strong downstre…
Endor: Hardware-Friendly Sparse Format for Offloaded LLM Inference
Donghyeon Joo, Ramyad Hadidi, Soheil Feizi +1
The increasing size of large language models (LLMs) challenges their usage on resource-constrained platforms. For example, memory on modern GPUs is insufficient to hold LLMs that a…