4 papers
The 2026 Algorithmic Information Theory Data Compression Challenge
André Ribeiro, Rúben Garrido, Violeta Ramos +28
Lossless data compression remains central to computer science, with direct impact on storage, communication bandwidth, computational cost, and energy consumption. It is also closel…
A two-step sequential approach for hyperparameter selection in finite context models
José Contente, Ana Martins, Armando J. Pinho +1
Finite-context models (FCMs) are widely used for compressing symbolic sequences such as DNA, where predictive performance depends critically on the context length k and smoothing p…
Decoding the Past: Explainable Machine Learning Models for Dating Historical Texts
Paulo J. N. Pinto, Armando J. Pinho, Diogo Pratas
Accurately dating historical texts is essential for organizing and interpreting cultural heritage collections. This article addresses temporal text classification using interpretab…
AIDetx: a compression-based method for identification of machine-learning generated text
Leonardo Almeida, Pedro Rodrigues, Diogo Magalhães +2
This paper introduces AIDetx, a novel method for detecting machine-generated text using data compression techniques. Traditional approaches, such as deep learning classifiers, ofte…