1 citations · 1 across the 9 of their papers we have counts for
11 papers
Refusing the Impossible: A Taxonomy and Benchmark for Code Hallucination in Large Language Models
Vishnu Asutosh Dasu, Ashish Kundu, Gang Tan
Large language models (LLMs) often produce code that looks plausible but is not grounded in reality. The code may import packages that do not exist or claim to implement algorithms…
Heimdall: Formally Verified Automated Migration of Legacy eBPF Programs to Rust
Vishnu Asutosh Dasu, Monika Santra, Md Rafi Ur Rashid +3
Extended Berkeley Packet Filter (eBPF) programs are kernel extensions used for networking, observability, and security enforcement in the Linux kernel. The in-kernel eBPF verifier…
Robustness of Vision Language Models Against Split-Image Harmful Input Attacks
Md Rafi Ur Rashid, MD Sadik Hossain Shanto, Vishnu Asutosh Dasu +1
Vision-Language Models (VLMs) are now a core part of modern AI. Recent work proposed several visual jailbreak attacks using single/ holistic images. However, contemporary VLMs demo…
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…
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Alireza Aghabagherloo, Aydin Abadi, Sumanta Sarkar +2
The accuracy and robustness of machine learning models against adversarial attacks are significantly influenced by factors such as training data quality, model architecture, the tr…
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…
Privacy-Preserving Data Deduplication for Enhancing Federated Learning of Language Models (Extended Version)
Aydin Abadi, Vishnu Asutosh Dasu, Sumanta Sarkar
Deduplication is a vital preprocessing step that enhances machine learning model performance and saves training time and energy. However, enhancing federated learning through dedup…
NeuFair: Neural Network Fairness Repair with Dropout
Vishnu Asutosh Dasu, Ashish Kumar, Saeid Tizpaz-Niari +1
This paper investigates neuron dropout as a post-processing bias mitigation for deep neural networks (DNNs). Neural-driven software solutions are increasingly applied in socially c…
Gradient-Free Privacy Leakage in Federated Language Models through Selective Weight Tampering
Md Rafi Ur Rashid, Vishnu Asutosh Dasu, Kang Gu +2
Federated learning (FL) has become a key component in various language modeling applications such as machine translation, next-word prediction, and medical record analysis. These a…