8 citations · 10 across the 4 of their papers we have counts for
4 papers · 1 filter
Accurate and Diverse LLM Mathematical Reasoning via Automated PRM-Guided GFlowNets
Adam Younsi, Ahmed Attia, Abdalgader Abubaker +3
Achieving both accuracy and diverse reasoning remains challenging for Large Language Models (LLMs) in complex domains like mathematics. A key bottleneck is evaluating intermediate…
PORT: Preference Optimization on Reasoning Traces
Salem Lahlou, Abdalgader Abubaker, Hakim Hacid
Preference optimization methods have been successfully applied to improve not only the alignment of large language models (LLMs) with human values, but also specific natural langua…
Data Quality in Edge Machine Learning: A State-of-the-Art Survey
Mohammed Djameleddine Belgoumri, Mohamed Reda Bouadjenek, Sunil Aryal +1
Data-driven Artificial Intelligence (AI) systems trained using Machine Learning (ML) are shaping an ever-increasing (in size and importance) portion of our lives, including, but no…
Training Machine Learning models at the Edge: A Survey
Aymen Rayane Khouas, Mohamed Reda Bouadjenek, Hakim Hacid +1
Edge computing has gained significant traction in recent years, promising enhanced efficiency by integrating artificial intelligence capabilities at the edge. While the focus has p…