Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Ex
Sparse Mixture-of-Experts (MoE) models have become an important approach for scaling Large Language Models (LLMs), but their inference efficiency depends strongly on expert activation patterns. Speculative decoding (SD) accelerates autoregr
https://arxiv.org/abs/2607.12696v1 ↗Thesis fit
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Within your typical scope; diligence still required.
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Light
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llm
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Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
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Jincheng Xie
1.0
low confidence
R
Runheng Liu
1.0
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H
Heyan Huang
1.0
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Y
Yawen Ling
1.0
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H
Hanbin Dai
1.0
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Y
Yu Zheng
1.0
low confidence
W
Wen Hu
1.0
low confidence
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