4 papers
REPRO: Reflective Evolutionary Prompt Optimizer for Automated LLM Red-Teaming
Abrar Alotaibi, Moataz Ahmed
Safety-aligned large language models (LLMs) remain vulnerable to adversarial prompts that bypass their safety training. Existing automated red-teaming methods either require privil…
LILA: Calibration-Free Structured Pruning of Large Language Models via Latent Spectral Geometry
Sankar Behera, Dhruv Singh, Anshika Agnihotri +3
Structured pruning of large language models (LLMs) offers hardware-efficient compression, yet existing methods require calibration data, gradient computation, or large auxiliary po…
ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification
Sankar Behera, Yamuna Prasad
Deep Neural Networks (DNNs) have achieved remarkable success but their large size poses deployment challenges. While various pruning techniques exist, many involve complex iterativ…
MisGUIDE : Defense Against Data-Free Deep Learning Model Extraction
Mahendra Gurve, Sankar Behera, Satyadev Ahlawat +1
The rise of Machine Learning as a Service (MLaaS) has led to the widespread deployment of machine learning models trained on diverse datasets. These models are employed for predict…