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Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets
Marianna Nezhurina, Tomer Porian, Giovanni Pucceti +4
In studies of transferable learning, scaling laws are obtained for various important foundation models to predict their properties and performance at larger scales. We show here ho…
Inverse Deep Learning Ray Tracing for Heliostat Surface Prediction
Jan Lewen, Max Pargmann, Mehdi Cherti +3
Concentrating Solar Power (CSP) plants play a crucial role in the global transition towards sustainable energy. A key factor in ensuring the safe and efficient operation of CSP pla…
Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models
Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti +1
Large Language Models (LLMs) are often described as instances of foundation models that possess strong generalization obeying scaling laws, and therefore transfer robustly across v…