Summary of Legent: Open Platform For Embodied Agents, by Zhili Cheng et al.
LEGENT: Open Platform for Embodied Agents
by Zhili Cheng, Zhitong Wang, Jinyi Hu, Shengding Hu, An Liu, Yuge Tu, Pengkai Li, Lei Shi, Zhiyuan Liu, Maosong Sun
First submitted to arxiv on: 28 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Robotics (cs.RO)
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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 LEGENT platform integrates Large Language Models (LLMs) and Large Multimodal Models (LMMs) to develop human-like embodied agents for complex real-life tasks in physical environments. The platform offers a dual approach consisting of an interactive 3D environment, a user-friendly interface, and a data generation pipeline leveraging advanced algorithms. Experimental results demonstrate the trained model’s generalization capabilities surpassing GPT-4V. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine developing robots that can learn and communicate like humans. A new platform called LEGENT makes this possible by combining powerful computer models with interactive environments. This means robots can learn to perform complex tasks, like navigating rooms or understanding spoken commands, in a more natural way. The platform’s design allows for easy development of these embodied agents, which is essential for creating robots that can work alongside humans. |
Keywords
» Artificial intelligence » Generalization » Gpt
