Summary of Grootvl: Tree Topology Is All You Need in State Space Model, by Yicheng Xiao et al.
GrootVL: Tree Topology is All You Need in State Space Model
by Yicheng Xiao, Lin Song, Shaoli Huang, Jiangshan Wang, Siyu Song, Yixiao Ge, Xiu Li, Ying Shan
First submitted to arxiv on: 4 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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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 The proposed GrootVL network leverages a dynamic tree topology to overcome the limitations of traditional sequence-based models, enabling stronger representation capabilities and improved long-range interactions. By recursively propagating features based on spatial relationships and input data, this multimodal framework can be applied to both visual and textual tasks, outperforming existing structured state space models in image classification, object detection, segmentation, and multiple textual tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The GrootVL network is a new way of processing information that helps computers understand long-range dependencies better. This is useful for many applications like image recognition, object detection, and natural language processing. The model uses a special graph structure to break down sequences into smaller chunks, allowing it to learn more effectively from the data. |
Keywords
» Artificial intelligence » Image classification » Natural language processing » Object detection
