newsReddit r/MachineLearningTrust 52 Β· CommunityPublished 13d agoLive Β· 12d ago
Proposed architecture for inferencing sparse MOE models increasing Active parameters using layered + linear decay. Succinct reasoning without any model training or fine tune. [p]
I ported MoE expert expansion to llama.cpp π Run MoE models with MORE routed experts than the native top-K (8->x), adaptive threshold, 99β50% influence decay, layer range. Runtime-only, all backends. Tested on Qwen 3.6 35B A4B+ https://github.com/vagrillo/llama.cpp/blob/moe-expansion/docs/moe-expansion.md submitted b
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it β so bad links are debuggable.
- PossiblePossibly related (embedding) Β· 54%PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition β
- PossiblePossibly related (embedding) Β· 53%DeaMoE: Efficient MoE Structure for Fast Small-Batch Decoding β
- PossiblePossibly related (embedding) Β· 51%InternLM/xtuner β
- PossiblePossibly related (embedding) Β· 48%dphnAI/aphrodite-engine β
- PossiblePossibly related (embedding) Β· 48%alibaba/rtp-llm β
