4 papers
iResolveX: Multi-Layered Indirect Call Resolution via Static Reasoning and Learning-Augmented Refinement
Monika Santra, Bokai Zhang, Mark Lim +3
Indirect call resolution remains a key challenge in reverse engineering and control-flow graph recovery, especially for stripped or optimized binaries. Static analysis is sound but…
Improving Noise Efficiency in Privacy-preserving Dataset Distillation
Runkai Zheng, Vishnu Asutosh Dasu, Yinong Oliver Wang +2
Modern machine learning models heavily rely on large datasets that often include sensitive and private information, raising serious privacy concerns. Differentially private (DP) da…
Chain-of-Thought Driven Adversarial Scenario Extrapolation for Robust Language Models
Md Rafi Ur Rashid, Vishnu Asutosh Dasu, Ye Wang +2
Large Language Models (LLMs) exhibit impressive capabilities, but remain susceptible to a growing spectrum of safety risks, including jailbreaks, toxic content, hallucinations, and…
Attention Pruning: Automated Fairness Repair of Language Models via Surrogate Simulated Annealing
Vishnu Asutosh Dasu, Md Rafi ur Rashid, Vipul Gupta +2
This paper explores pruning attention heads as a post-processing bias mitigation method for large language models (LLMs). Modern AI systems such as LLMs are expanding into sensitiv…