ShortOPD: Recovering Pruned LLMs with Short-to-Long On-Policy Distillation
Structured pruning is a hardware-friendly way to compress LLMs, but it is mostly validated on multiple-choice recognition tasks, while the same compressed checkpoints can collapse on the free-form generation that deployment actually require
https://arxiv.org/abs/2607.13124v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
Light
How close the company’s idea is to your thesis statement
Sector
llm
Overlap with sectors you care about
Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↓ declining
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Correct facts used on the next screening or memo.
People
Q
Qingyu Zhang
1.0
low confidence
Q
Qianhao Yuan
1.0
low confidence
H
Hongyu Lin
1.0
low confidence
Y
Yaojie Lu
1.0
low confidence
X
Xianpei Han
1.0
low confidence
L
Le Sun
1.0
low confidence
X
Xiang Li
1.0
low confidence
M
Ming Xu
1.0
low confidence
J
Jiarui Li
1.0
low confidence
X
Xiuyin Zhao
1.0
low confidence
Activity & evidence
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