Abdelhakim Benechehab

According to our database, Abdelhakim Benechehab authored at least 9 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning.

Giuseppe Paolo, Abdelhakim Benechehab, Hamza Cherkaoui, Albert Thomas, Balázs Kégl

CoRR, February, 2025

AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting.

Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

CoRR, February, 2025

Zero-shot Model-based Reinforcement Learning using Large Language Models.

Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat, Oussama Zekri, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Ievgen Redko, Balázs Kégl

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level.

Antoine Grosnit, Alexandre Maraval, James Doran, Giuseppe Paolo, Albert Thomas, Refinath Shahul Hameed Nabeezath Beevi, Jonas Gonzalez, Khyati Khandelwal, Ignacio Iacobacci, Abdelhakim Benechehab, Hamza Cherkaoui, Youssef Attia El Hili, Kun Shao, Jianye Hao, Jun Yao, Balázs Kégl, Haitham Bou-Ammar, Jun Wang

CoRR, 2024

Large Language Models as Markov Chains.

Oussama Zekri, Ambroise Odonnat, Abdelhakim Benechehab, Linus Bleistein, Nicolas Boullé, Ievgen Redko

CoRR, 2024

Can LLMs predict the convergence of Stochastic Gradient Descent?

Oussama Zekri, Abdelhakim Benechehab, Ievgen Redko

CoRR, 2024

A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning.

Abdelhakim Benechehab, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Balázs Kégl

CoRR, 2024

Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning.

Abdelhakim Benechehab, Albert Thomas, Balázs Kégl

CoRR, 2024

2023

Multi-timestep models for Model-based Reinforcement Learning.

Abdelhakim Benechehab, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

CoRR, 2023