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cs.LG2026
Interfaces and Modules: A Scalable Representation for Weight-Space Learning across Architectures
Michał Kozyra, Michael Bronstein
Weight-space learning across architectures requires representations that respect parameter symmetries and scale to large networks. Existing equivariant tensor encoders require arch…
cs.LG2026
Training Transformers for KV Cache Compressibility
Yoav Gelberg, Yam Eitan, Michael Bronstein +2
Long-context language modeling is increasingly constrained by the Key-Value (KV) cache, whose memory and decode-time access costs scale linearly with the prefix length. This bottle…