12 citations · 18 across the 12 of their papers we have counts for
4 papers · 1 filter
Active Membership Inference Test (aMINT): Enhancing Model Auditability with Multi-Task Learning
Daniel DeAlcala, Aythami Morales, Julian Fierrez +3
Active Membership Inference Test (aMINT) is a method designed to detect whether given data were used during the training of machine learning models. In Active MINT, we propose a no…
AttZoom: Attention Zoom for Better Visual Features
Daniel DeAlcala, Aythami Morales, Julian Fierrez +1
We present Attention Zoom, a modular and model-agnostic spatial attention mechanism designed to improve feature extraction in convolutional neural networks (CNNs). Unlike tradition…
Is My Text in Your AI Model? Gradient-based Membership Inference Test applied to LLMs
Gonzalo Mancera, Daniel DeAlcala, Julian Fierrez +2
This work adapts and studies the gradient-based Membership Inference Test (gMINT) to the classification of text based on LLMs. MINT is a general approach intended to determine if g…
MINT-Demo: Membership Inference Test Demonstrator
Daniel DeAlcala, Aythami Morales, Julian Fierrez +3
We present the Membership Inference Test Demonstrator, to emphasize the need for more transparent machine learning training processes. MINT is a technique for experimentally determ…