Guo-Xia Wang

Distributed attention can achieve near-zero communication overhead for mask localization and compute-communication overlap, unlocking massive throughput gains for long-context LLMs.

A novel attention mechanism slashes KV cache by 4x and training FLOPs by 7.9% while *improving* LLM quality, breaking the long-context "impossible triangle."