3 papers
cs.CV2025
Erasing CLIP Memories: Non-Destructive, Data-Free Zero-Shot class Unlearning in CLIP Models
Ashish Mishra, Tarun Kumar, Gyanaranjan Nayak +3
We introduce a novel, closed-form approach for selective unlearning in multimodal models, specifically targeting pretrained models such as CLIP. Our method leverages nullspace proj…
cs.CV2025
Selective, Controlled and Domain-Agnostic Unlearning in Pretrained CLIP: A Training- and Data-Free Approach
Ashish Mishra, Gyanaranjan Nayak, Tarun Kumar +3
Pretrained models like CLIP have demonstrated impressive zero-shot classification capabilities across diverse visual domains, spanning natural images, artistic renderings, and abst…
cs.LG2024
Data Efficient Evaluation of Large Language Models and Text-to-Image Models via Adaptive Sampling
Cong Xu, Gayathri Saranathan, Mahammad Parwez Alam +5
Evaluating LLMs and text-to-image models is a computationally intensive task often overlooked. Efficient evaluation is crucial for understanding the diverse capabilities of these m…