Sequel to: Learning to Skip Blocks: Self-Discovered Ultrametric Routing for Hardware-Accelerated Sparse Attention Abstract We present Llama Surgery, a method for injecting learned block-sparse attention topologies into pre-trained dense language models…

Abstract. Standard dense self-attention scales quadratically in sequence length, creating an intractable memory and compute bottleneck for long-context Transformers. We introduce Dynamic Ultrametric Attention, a framework in which a Transformer autonom…

This is a Collaborative Work https://github.com/sneed-and-feed/INCARNATE-SOPHIA-5.0/ submitted by /u/LooseSwing88 [link] [comments]