Linear Reusable Neural Bases Architecture for Network Compression.

arXiv:2609.01550v3 Announce Type: replace-cross Abstract: Memory constraints remain a critical bottleneck in the deployment of large-scale AI models. Parameter sharing across network depth reduces model storage, but repeatedly applying an identical transformat