MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivari
Mobile usage traces are critical for tasks such as user behavior prediction and app recommendation, yet their use is constrained by privacy restrictions and costly large-scale data collection. Although generative models perform well on gene
https://arxiv.org/abs/2607.14249v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
None
How close the company’s idea is to your thesis statement
Sector
ai
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 ↑ improving
▸ Add / edit details
Correct facts used on the next screening or memo.
People
Y
Yilai Liu
1.0
low confidence
S
Shiyuan Zhang
1.0
low confidence
H
Hongyang Du
1.0
low confidence
Christopher Farm
Amir Manji