Summary of Aflow: Automating Agentic Workflow Generation, by Jiayi Zhang et al.
AFlow: Automating Agentic Workflow Generation
by Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, Fengwei Teng, Xionghui Chen, Jiaqi Chen, Mingchen Zhuge, Xin Cheng, Sirui Hong, Jinlin Wang, Bingnan Zheng, Bang Liu, Yuyu Luo, Chenglin Wu
First submitted to arxiv on: 14 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG); Software Engineering (cs.SE)
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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 This research paper proposes a new framework called AFlow, which automates the generation and optimization of complex workflows using large language models (LLMs). The authors reformulate workflow optimization as a search problem over code-represented workflows and introduce an automated framework that efficiently explores this space using Monte Carlo Tree Search. The framework iteratively refines workflows through code modification, tree-structured experience, and execution feedback. Empirical evaluations across six benchmark datasets demonstrate AFlow’s efficacy, yielding a 5.7% average improvement over state-of-the-art baselines. Furthermore, AFlow enables smaller models to outperform GPT-4o on specific tasks at 4.55% of its inference cost in dollars. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper develops an automated workflow generator called AFlow that uses large language models (LLMs) to solve complex problems. Right now, people have to create these workflows step-by-step, which is time-consuming and limits what can be done. The researchers want to make it easier by using AI to generate the workflows automatically. They created a new way of searching for good workflows, which involves modifying code, learning from experience, and getting feedback from executing the workflow. This method works better than previous methods and can even help smaller models perform as well as larger ones on certain tasks. |
Keywords
» Artificial intelligence » Gpt » Inference » Optimization
