Summary of Mammothmoda: Multi-modal Large Language Model, by Qi She and Junwen Pan and Xin Wan and Rui Zhang and Dawei Lu and Kai Huang
MammothModa: Multi-Modal Large Language Model
by Qi She, Junwen Pan, Xin Wan, Rui Zhang, Dawei Lu, Kai Huang
First submitted to arxiv on: 26 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces MammothModa, a multi-modal large language model (MLLM) designed to achieve state-of-the-art performance from an elementary baseline. The design focuses on three key insights: integrating visual capabilities with complex language understanding, extending the context window for high-resolution and long-duration visual features, and curating high-quality bilingual datasets to reduce visual hallucinations. MammothModa consistently outperforms state-of-the-art models like LLaVA-series across real-world visual language benchmarks without relying on bells and whistles. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MammothModa is a new kind of computer program that can understand both text and images really well. The researchers made three important discoveries to make it work better: they added special parts that help the program understand what’s in pictures, they found a way to deal with very detailed images, and they created a big collection of images and words for the program to practice with. This new program is able to do better than others like it on tests that check how well it can understand language and pictures. |
Keywords
» Artificial intelligence » Context window » Language understanding » Large language model » Multi modal
