Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn
Multi-modal Large Language Models (MLLMs) have made substantial advances on benchmarks, yet their real-world effectiveness remains uncertain. This gap stems from the fundamental misalignment between benchmarks in controlled, static settings
https://arxiv.org/abs/2607.14499v1 ↗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
llm, ai
Overlap with sectors you care about
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Outside
Outside your target regions — 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
Y
Yijiang Li
2.0
low confidence
H
Huiqi Zou
US
3.0
low confidence
B
Bingyang Wang
2.0
low confidence
Z
Ziang Xiao
2.0
low confidence