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Talent Scout
Y
Yu Zeng
University of Science and Technology of China
Q
Qiuchen Wang
University of Science and Technology of China
Z
Zhen Fang
University of Science and Technology of China
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Founder's Pitch
"Vision-DeepResearch offers a robust long-horizon reasoning engine for multimodal queries, surpassing existing language models in accuracy and depth."
Commercial Viability Breakdown
0-10 scaleHigh Potential
2/4 signals
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4/4 signals
Series A Potential
2/4 signals
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Why It Matters
This research addresses the limitations of existing multimodal models in handling complex, fact-intensive queries that make use of both text and visual data. Without it, users may struggle with inaccurate or incomplete search results in noisy environments.
Product Angle
A cloud-based API or widget that enterprises can integrate to enhance their internal knowledge tools, supporting complex query reconciliation and verification tasks.
Disruption
It could replace or augment current search and retrieval systems, providing a higher accuracy and reliability alternative to existing multimodal search engines.
Product Opportunity
Large potential market in enterprise knowledge management systems, particularly focused on industries like media, market research, and any segment needing robust data verification and narrative synthesis.
Use Case Idea
An API service for enterprises that need reliable, story-driven content generation from complex multimedia inputs, particularly useful in journalism and market intelligence.
Science
Vision-DeepResearch enhances multimodal LLMs by incorporating a deep, iterative search process that adapts to noisy environments, using multi-turn interactions and reinforcement learning to gather and verify evidence across text and image sources.
Method & Eval
The model was tested against six established benchmarks and outperformed prior systems significantly, suggesting strong direct applications in real-world environments.
Caveats
Potential issues include high computation demands and integration complexity with existing enterprise systems, as well as reliance on external data which may introduce variability.
Author Intelligence
Wenxuan Huang
CUHK MMLab, East China Normal University
wxhuang0616@gmail.com
Yu Zeng
University of Science and Technology of China
Qiuchen Wang
University of Science and Technology of China
Zhen Fang
University of Science and Technology of China
Shaosheng Cao
Xiaohongshu Inc.
Zheng Chu
Harbin Institute of Technology
Qingyu Yin
Zhejiang University
Shuang Chen
University of California, Los Angeles
Zhenfei Yin
University of Oxford
Lin Chen
University of Science and Technology of China
Zehui Chen
University of Science and Technology of China
Yao Hu
Xiaohongshu Inc.
Philip Torr
University of Oxford
Feng Zhao
University of Science and Technology of China
Wanli Ouyang
CUHK MMLab, Shenzhen Loop Area Institute