Title: Kwai Summary Attention Technical Report

Source: http://arxiv.org/abs/2604.24432v1

Summary:

Kwai Summary Attention (KSA) introduces a novel architectural primitive that compresses historical context into learnable summary tokens, enabling a O(n/k) complexity for long-context sequence modeling. This approach provides a foundational new path for scaling next-generation LLMs by trading minimal memory for interpretable, semantic-level retention of long-range dependencies.