Summary of Mio: a Foundation Model on Multimodal Tokens, by Zekun Wang et al.
MIO: A Foundation Model on Multimodal Tokens
by Zekun Wang, King Zhu, Chunpu Xu, Wangchunshu Zhou, Jiaheng Liu, Yibo Zhang, Jiashuo Wang, Ning Shi, Siyu Li, Yizhi Li, Haoran Que, Zhaoxiang Zhang, Yuanxing Zhang, Ge Zhang, Ke Xu, Jie Fu, Wenhao Huang
First submitted to arxiv on: 26 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 MIO is a novel foundation model that can understand and generate speech, text, images, and videos in an end-to-end, autoregressive manner. It’s trained on a mixture of discrete tokens across four modalities using causal multimodal modeling. The model undergoes a four-stage training process: alignment pre-training, interleaved pre-training, speech-enhanced pre-training, and comprehensive supervised fine-tuning on diverse textual, visual, and speech tasks. MIO exhibits competitive and sometimes superior performance compared to previous baselines, including dual-modal, any-to-any, and modality-specific models. It also demonstrates advanced capabilities such as interleaved video-text generation, chain-of-visual-thought reasoning, and instructional image editing. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MIO is a special kind of AI model that can understand and create different kinds of media like speech, text, pictures, and videos. This is important because it means the model can learn from and generate many types of information at once. The model is trained using a specific way of combining data from four different sources: text, images, videos, and audio. MIO’s training process involves several stages to help it learn how to understand and create different kinds of media. When tested against other models, MIO performed well and even outperformed some of them in certain tasks. This new AI model has many useful capabilities, such as creating mixed media like video-text sequences or generating images based on text prompts. |
Keywords
» Artificial intelligence » Alignment » Autoregressive » Fine tuning » Supervised » Text generation
