7 citations · 12 across the 11 of their papers we have counts for
13 papers
Fetch Me If You Can: A Comprehensive Analysis of Fetch Metadata
Pedro Bernardo, Alex Ploner, Marco Squarcina +2
Effective server-side defenses against cross-site attacks depend on understanding the context in which browser requests are generated. However, servers often lack the information n…
Just rephrase it! Uncertainty estimation in closed-source language models via multiple rephrased queries
Adam Yang, Chen Chen, Konstantinos Pitas
State-of-the-art large language models are sometimes distributed as open-source software but are also increasingly provided as a closed-source service. These closed-source large-la…
Just rotate it! Uncertainty estimation in closed-source models via multiple queries
Konstantinos Pitas, Julyan Arbel
We propose a simple and effective method to estimate the uncertainty of closed-source deep neural network image classification models. Given a base image, our method creates multip…
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data
Konstantinos Pitas, Julyan Arbel
We present a method to improve the calibration of deep ensembles in the small training data regime in the presence of unlabeled data. Our approach is extremely simple to implement:…
A Primer on Bayesian Neural Networks: Review and Debates
Julyan Arbel, Konstantinos Pitas, Mariia Vladimirova +1
Neural networks have achieved remarkable performance across various problem domains, but their widespread applicability is hindered by inherent limitations such as overconfidence i…
The fine print on tempered posteriors
Konstantinos Pitas, Julyan Arbel
We conduct a detailed investigation of tempered posteriors and uncover a number of crucial and previously undiscussed points. Contrary to previous results, we first show that for r…