Active Real-World Factor-Based Evaluation for Generalist Robot Policies
Generalist robot manipulation policies trained on large, diverse datasets have shown remarkable promise across a wide range of tasks. However, rigorously evaluating these policies remains a fundamental challenge. Real-world performance depe
https://arxiv.org/abs/2607.14439v1 ↗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 ↓ declining
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Correct facts used on the next screening or memo.
People
A
Andrew Liao
1.0
low confidence
H
Hanchen Cui
1.0
low confidence
K
Karthik Desingh
1.0
low confidence
A
Aryan Deshwal
1.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
Claire Mao
Lucy Cai
Cortex AI
· Active
Large-scale real-world robot & human data for embodied AI
founders not scraped yet