Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns
DGX agentarXiv:2606.25010v1 Announce Type: cross Abstract: Neural scaling laws for transformer language models predict smooth improvements in pretraining loss with increasing parameters, but downstream capabil