Stop Thinking, Start Looking: Efficient Post-Training for Multimodal Document Qu
Efficient multimodal document question answering with explicit visual grounding, locating the precise document region that supports each answer remains an open challenge. Current approaches bifurcate into Supervised Fine-Tuning (SFT), which
https://arxiv.org/abs/2607.14682v1 ↗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
H
Harikrishnan P M
2.0
low confidence
G
Goutham Vignesh
2.4
low confidence
G
Ganesh Parab
2.0
low confidence
S
Saisubramaniam Gopalakrishnan
2.0
low confidence
V
Vishal Vaddina
2.0
low confidence
V
Varun V
1.0
low confidence
R
Rohit Agrawal
2.0
low confidence
V
V Varun
1.0
low confidence