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cs.LG2024
On Calibration in Multi-Distribution Learning
Rajeev Verma, Volker Fischer, Eric Nalisnick
Modern challenges of robustness, fairness, and decision-making in machine learning have led to the formulation of multi-distribution learning (MDL) frameworks in which a predictor…
cs.LG2023★ 3 cited
Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems
David T. Hoffmann, Simon Schrodi, Jelena Bratulić +3
In this work, we study rapid improvements of the training loss in transformers when being confronted with multi-step decision tasks. We found that transformers struggle to learn th…