Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs
Despite the rapid progress of Multimodal Large Language Models (MLLMs), they still suffer from untruthfulness issues, such as visual hallucinations, content fabrication, and unfaithful reasoning, which substantially undermine their faithful
https://arxiv.org/abs/2607.13712v1 ↗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
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
▸ Add / edit details
Correct facts used on the next screening or memo.
People
Z
Zhixiao Zheng
1.0
low confidence
Z
Zheren Fu
1.0
low confidence
Z
Zhiyuan Yao
1.0
low confidence
C
Chunxiao Liu
1.0
low confidence
D
Dongming Zhang
1.0
low confidence
Z
Zhendong Mao
1.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
Daily
· Active
Conversational Voice and Multimodal AI built with Open Source
founders not scraped yet