Summary of Turn Every Application Into An Agent: Towards Efficient Human-agent-computer Interaction with Api-first Llm-based Agents, by Junting Lu et al.
Turn Every Application into an Agent: Towards Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents
by Junting Lu, Zhiyang Zhang, Fangkai Yang, Jue Zhang, Lu Wang, Chao Du, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
First submitted to arxiv on: 25 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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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 AXIS framework is a novel approach to large language model-based agents that prioritizes actions through application programming interfaces (APIs) over user interface (UI) interactions. This framework aims to reduce latency and improve reliability by automating the exploration of applications and creating APIs. The authors demonstrate the effectiveness of AXIS on Office Word, achieving a 65%-70% reduction in task completion time, a 38%-53% decrease in cognitive workload, while maintaining accuracy of 97%-98% comparable to human performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The AXIS framework is a new way for computers and humans to interact. It uses large language models to help machines understand how to use different applications, making them more efficient and reliable. The authors tested this approach on Microsoft Word and found that it worked much better than before, taking less time and effort from users while still being just as accurate. |
Keywords
» Artificial intelligence » Large language model
