3 papers
cs.LG2026
Discovering Symmetries in Neural Network Parameter Spaces
Bo Zhao, Nima Dehmamy, Robin Walters +1
Parameter space symmetries are important for understanding neural networks' loss landscape, training dynamics, and generalization. However, systematically identifying these symmetr…
cs.CY2026
Billions of Sketches Reveal Hidden Cultural Variation in Human Concepts
Arianna Pera, Mauro Martino, Nima Dehmamy +3
Claims about the universality of human concepts have been predominantly assessed through linguistic similarity across languages and cultures. However, words are effective as commun…
cs.AI2026
Flow Reasoning Models: Turning Flows Into Efficient Recurrent Reasoners
Alec Helbling, Andrey Bryutkin, Mauro Martino +3
Structured reasoning requires making and revising interdependent decisions to reach a globally consistent solution. Existing architectures struggle with this: autoregressive models…