As Large Language Models quickly become ubiquitous, it becomes critical ...
Neural networks for computer vision extract uninterpretable features des...
With the rise of Large Language Models (LLMs) and their ubiquitous deplo...
As LLMs become commonplace, machine-generated text has the potential to ...
Watermarking the outputs of generative models is a crucial technique for...
The strength of modern generative models lies in their ability to be
con...
Potential harms of large language models can be mitigated by watermarkin...
As industrial applications are increasingly automated by machine learnin...
Federated learning is particularly susceptible to model poisoning and
ba...
Reconstruction of a continuous surface of two-dimensional manifold from ...
Federated learning (FL) has rapidly risen in popularity due to its promi...
A central tenet of Federated learning (FL), which trains models without
...
Deep generative networks in recent years have reinforced the need for ca...
Shape modeling and reconstruction from raw point clouds of objects stand...
Many learning-based approaches have difficulty scaling to unseen data, a...
The problem of adversarial examples has shown that modern Neural Network...
Recent studies show that machine learning models are vulnerable to
adver...
In this paper, we introduce the algorithms of Orthogonal Deep Neural Net...