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
Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
Sparse adversarial attack for generating interpretable adversarial examples.
Jan 1, 2025
Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning
A neurosymbolic AI framework for robust network intrusion detection with uncertainty quantification.
Jan 1, 2025
Neurosymbolic AI for network intrusion detection systems: A survey
A comprehensive survey of neurosymbolic AI approaches for network intrusion detection systems.
Jan 1, 2025
Constrained Edge AI Deployment: Fine-Tuning vs Distillation for LLM Compression
Comparing fine-tuning vs distillation for LLM compression in edge AI deployment.
Jan 1, 2025
Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo
Aug 1, 2023
Reducing classifier overconfidence against adversaries through graph algorithms
Jul 1, 2023
Enhancing Resilience in Mobile Edge Computing Under Processing Uncertainty
Mar 1, 2023
Maximizing Energy Efficiency With Channel Uncertainty Under Mutual Interference
Oct 1, 2022
URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference Methods
URSABench is an open-source benchmarking suite for assessing Bayesian deep learning models and inference methods, focusing on uncertainty quantification, robustness, scalability, and accuracy in classification tasks for both server and edge GPUs.
Apr 1, 2022