Massive Activations in Hybrid Linear Attention LLMs: Spikes and Plateaus
startlux-models · hf · 2026-08-14
This research investigates the phenomenon of massive activations in hybrid linear-attention Large Language Models.
The study reveals that these activations exhibit pre-attention spikes and inter-spike plateaus governed by cancellation timing. Furthermore, the morphology recovers when approaching the full-attention limit.
Related event: New Study Unveils Inner Workings of Hybrid Linear-Attention LLMs(2 posts)→
More from Research
- Quiz: Double the Residual Stream from 4096 to 8192 — How Does Param Count Change? — Sauers_ · 2026-10-16
- Researcher credits GPT for multiple accepted papers, incl. disproving Wegner's 1965 conjecture — ctjlewis · 2026-10-16
- Open-source shopper attention heatmap: YOLO11-pose + Gaze-LLE + Depth Anything V2 — claudioe · 2026-10-16
- AutoAgent0: VLM-powered agentic runtime lifts long-tail driving success by 28.3pp — yining_hong · 2026-10-16
- Shuffled labels hit AUC 0.59: selection bias, not signal, drives prosody benchmarks — maier_ak · 2026-10-16
- CODESTRUCT reframes codebases as AST action spaces to fix brittle LLM code agents — burkov · 2026-10-16