39 citations · 51 across the 25 of their papers we have counts for
7 papers · 1 filter
Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations
Joel Brogan, Olivera Kotevska, Anibely Torres +2
Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in t…
Jailbreaking Large Language Models with Symbolic Mathematics
Emet Bethany, Mazal Bethany, Juan Arturo Nolazco Flores +2
Recent advancements in AI safety have led to increased efforts in training and red-teaming large language models (LLMs) to mitigate unsafe content generation. However, these safety…
AutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing
Ana Nunez, Nafis Tanveer Islam, Sumit Kumar Jha +1
Recent advancements in automatic code generation using large language models (LLMs) have brought us closer to fully automated secure software development. However, existing approac…
Data Augmentation for Image Classification using Generative AI
Fazle Rahat, M Shifat Hossain, Md Rubel Ahmed +2
Scaling laws dictate that the performance of AI models is proportional to the amount of available data. Data augmentation is a promising solution to expanding the dataset size. Tra…
Development and Validation of Fully Automatic Deep Learning-Based Algorithms for Immunohistochemistry Reporting of Invasive Breast Ductal Carcinoma
Sumit Kumar Jha, Purnendu Mishra, Shubham Mathur +4
Immunohistochemistry (IHC) analysis is a well-accepted and widely used method for molecular subtyping, a procedure for prognosis and targeted therapy of breast carcinoma, the most…
Multi-Stain Multi-Level Convolutional Network for Multi-Tissue Breast Cancer Image Segmentation
Akash Modi, Sumit Kumar Jha, Purnendu Mishra +4
Digital pathology and microscopy image analysis are widely employed in the segmentation of digitally scanned IHC slides, primarily to identify cancer and pinpoint regions of intere…
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
Kavita Kumari, Murtuza Jadliwala, Sumit Kumar Jha +1
Model explanations improve the transparency of black-box machine learning (ML) models and their decisions; however, they can also be exploited to carry out privacy threats such as…