Author

Bardh Prenkaj

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#artificial intelligence Preprint Oct 2026

Co-Recursive Semantic Self-Extension: A Mathematical Foundation for Open-Ended Intelligence

Artificial intelligence has advanced through scale, data, and computation, yet remains bounded by its representational framework. We ask what makes intelligence open-ended. Every inferential system selects meaningful distinctions, limiting what it can learn. Within a fixed purpose, performance reaches a ceiling set by...

Simon Hegelich, Bardh Prenkaj, Habiba Sarhan et al. · 0 citations

#machine learning Preprint Sep 2026

High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability

A CPD framework that improves scalability and interpretability by leveraging the Sliced Wasserstein (SW) distance and produces interpretable change-point annotations, making it practical for deployment in high-stakes applications.

Sven Jacob, Bardh Prenkaj, Wei-Jia Shao et al. · 0 citations

Jul 2026

Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning

A principled reward decomposition framework is introduced that decouples verifiability from sparsity, and two new reward functions are proposed: an exponential reward that provides graded penalties based on the count of forbidden-concept occurrences, and a PageRank inspired reward that weights penalties by semantic imp...

Efstratios Zaradoukas, Davide Gabrielli, Bardh Prenkaj et al. · arXiv.org · 1 citation