Multi-timestep models for Model-based Reinforcement Learning. - Abdelhakim Benechehab; Giuseppe Paolo; Albert Thomas 001; Maurizio Filippone; Balázs Kégl (CoRR, 2023)

Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning. - Abdelhakim Benechehab; Albert Thomas 001; Balázs Kégl (CoRR, 2024)

A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning. - Abdelhakim Benechehab; Albert Thomas 001; Giuseppe Paolo; Maurizio Filippone; Balázs Kégl (CoRR, 2024)

Can LLMs predict the convergence of Stochastic Gradient Descent? - Oussama Zekri; Abdelhakim Benechehab; Ievgen Redko (CoRR, 2024)

Large Language Models as Markov Chains. - Oussama Zekri; Ambroise Odonnat; Abdelhakim Benechehab; Linus Bleistein; Nicolas Boullé; Ievgen Redko (CoRR, 2024)

Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level. - Antoine Grosnit; Alexandre Maraval; James Doran; Giuseppe Paolo; Albert Thomas 001; Refinath Shahul Hameed Nabeezath Beevi; Jonas Gonzalez; Khyati Khandelwal; Ignacio Iacobacci; Abdelhakim Benechehab; Hamza Cherkaoui; Youssef Attia El Hili; et al. (CoRR, 2024)

Zero-shot Model-based Reinforcement Learning using Large Language Models. - Abdelhakim Benechehab; Youssef Attia El Hili; Ambroise Odonnat; Oussama Zekri; Albert Thomas 001; Giuseppe Paolo; Maurizio Filippone; Ievgen Redko; Balázs Kégl (ICLR, 2025)

AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting. - Abdelhakim Benechehab; Vasilii Feofanov; Giuseppe Paolo; Albert Thomas 001; Maurizio Filippone; Balázs Kégl (CoRR, 2025)

TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning. - Giuseppe Paolo; Abdelhakim Benechehab; Hamza Cherkaoui; Albert Thomas 001; Balázs Kégl (CoRR, 2025)