2 papers
cs.RO2026
AutoRSR: Automated Real-to-Sim-to-Real Data Generation for Scalable Robot Learning
Jiawei Zhang, Chang Liu, Litao Deng +2
Scaling embodied robot learning requires large and diverse manipulation datasets, but collecting real-world demonstrations remains expensive in human effort and robot time. Simulat…
cs.LG2025
Transformers Provably Learn Sparse XOR with Polylogarithmic Parameters
Yaomengxi Han, Debarghya Ghoshdastidar
Learning sparse parity functions has become a theoretical testbed for studying feature learning in neural networks. However, existing analyses primarily focus on Feed-Forward Neura…