eeworldonline

How can you protect against adversarial prompting in generative AI?

Adversarial prompting refers to the practice of giving a large language model (LLM) contradictory or confusing instructions to bypass its safety measures or to elicit a specific, often harmful or ...
Bitdefender

Adversarial Training in Machine Learning

Adversarial training is a machine learning technique that improves a model's ability to resist attacks by using deceptive inputs during training. These examples are subtly altered to provoke mistakes, ...
GitHub

cjy24/fair-adversarial-training

While numerous work has been proposed to address fairness in machine learning, existing methods do not guarantee fair predictions under imperceptible feature perturbation, and a seemingly fair model ...
GitHub

Adversarial Training Improves Transferability

This project aims to reproduce the core experiments from the NIPS paper "Do Adversarially Robust ImageNet Models Transfer Better?", exploring the impact of Adversarial Training on model ...
VentureBeat

Adversarial training reduces safety of neural networks in robots: Research

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. There’s a growing interest in employing autonomous mobile ...
IEEE

Fast Adversarial Training With Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos

Abstract: Adversarial Training (AT) has been shown to significantly enhance adversarial robustness via a min-max optimization approach. However, its effectiveness in video recognition tasks is ...
ascopubs.org

Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology

HealthTree Cure Hub: A Patient-Derived, Patient-Driven Clinical Cancer Information Platform Used to Overcome Hurdles and Accelerate Research in Multiple Myeloma Adversarial images represent a ...