1 citations · 1 across the 4 of their papers we have counts for
5 papers
On the Extreme Variance of Certified Local Robustness Across Model Seeds
Minh Le, Phuong Cao
Robustness verification of neural networks, referring to formally proving that neural networks satisfy robustness properties, is of crucial importance in safety-critical applicatio…
Subliminal Learning: Language models transmit behavioral traits via hidden signals in data
Alex Cloud, Minh Le, James Chua +5
We study subliminal learning, a surprising phenomenon where language models transmit behavioral traits via semantically unrelated data. In our main experiments, a "teacher" model w…
Exploring the Adversarial Capabilities of Large Language Models
Lukas Struppek, Minh Hieu Le, Dominik Hintersdorf +1
The proliferation of large language models (LLMs) has sparked widespread and general interest due to their strong language generation capabilities, offering great potential for bot…
Efficacy of Neural Prediction-Based Zero-Shot NAS
Minh Le, Nhan Nguyen, Ngoc Hoang Luong
In prediction-based Neural Architecture Search (NAS), performance indicators derived from graph convolutional networks have shown remarkable success. These indicators, achieved by…
Robust Deep Neural Networks Inspired by Fuzzy Logic
Minh Le
Deep neural networks have achieved impressive performance and become the de-facto standard in many tasks. However, troubling phenomena such as adversarial and fooling examples sugg…