Attention-residuals, depth-wise cross-layer & Multiscreen softmax replacement
Key Questions
What is Multiscreen and its advantages?
Multiscreen replaces softmax with threshold screening, reducing parameters by 40% and achieving 3.2x speedup at 100K context. It optimizes attention for faster LLMs.
How does Moonshot/Kimi attention compare to residuals?
Moonshot/Kimi/MoDA attention outperforms residuals by about 1.25x. This shift improves efficiency in attention mechanisms.
What is the status of attention-residuals and Multiscreen?
These are in promotional/early stages; reproducibility, stability, and throughput are pending. Techniques like HISA and RWKV v8 are related for long-context gains.
Moonshot/Kimi/MoDA attention>residuals (~1.25x); Multiscreen (threshold screening no-softmax: 40% fewer params/3.2x 100K); Attention Editing (cross-arch efficiency); HISA (3.75x 64K); RWKV v8/Kimi Linear. Status: promotional/early; reproducibility/stability/throughput pending.
Sources (2)
Updated Apr 9, 2026