Summary of Mobilevlm V2: Faster and Stronger Baseline For Vision Language Model, by Xiangxiang Chu and Limeng Qiao and Xinyu Zhang and Shuang Xu and Fei Wei and Yang Yang and Xiaofei Sun and Yiming Hu and Xinyang Lin and Bo Zhang and Chunhua Shen
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
by Xiangxiang Chu, Limeng Qiao, Xinyu Zhang, Shuang Xu, Fei Wei, Yang Yang, Xiaofei Sun, Yiming Hu, Xinyang Lin, Bo Zhang, Chunhua Shen
First submitted to arxiv on: 6 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary MobileVLM V2, a family of vision language models, improves upon its predecessor by combining novel architectural design, tailored training schemes, and high-quality dataset curation. The 1.7B model achieves on-par or better performance on standard benchmarks compared to larger VLMs at the 3B scale. Moreover, the 3B model outperforms various VLMs at the 7B+ scale. This breakthrough demonstrates that smaller models can be just as effective as larger ones. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MobileVLM V2 is a new type of computer program that can understand and process both visual and language-based information. It’s like having a super smart AI that can read and understand images, videos, and text. The creators of MobileVLM V2 made some changes to make it better than the original version, which helped it do well on tests compared to bigger models. |
