Adversarial Machine Learning

Hydra: An Agentic Reasoning Approach for Enhancing Adversarial Robustness and Mitigating Hallucinations in Vision-Language Models

An agentic reasoning approach for enhancing robustness and reducing hallucinations in vision-language models.

Jul 1, 2025

ORCA: Agentic Reasoning For Hallucination and Adversarial Robustness in Vision-Language Models

An agentic reasoning framework for improving factual accuracy and adversarial robustness in vision-language models.

Jan 15, 2025

Towards Interpretable Adversarial Examples via Sparse Adversarial Attack

Sparse adversarial attack for generating interpretable adversarial examples.

Jan 1, 2025

Reducing classifier overconfidence against adversaries through graph algorithms

Jul 1, 2023

Adversarial Machine Learning: A New Threat Paradigm for Next-generation Wireless Communications

Jan 1, 2023

Runtime Monitoring of Deep Neural Networks Using Top-Down Context Models Inspired by Predictive Processing and Dual Process Theory

Jan 1, 2022

Trinity: Trust, Resilience and Interpretability of Machine Learning Models

Jan 1, 2021

Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification

Jan 1, 2020

Adversarial Distillation of Bayesian Neural Networks

Jan 1, 2020

Attribution-driven causal analysis for detection of adversarial examples

Jan 1, 2019