[2024 Best AI Paper] Agent Workflow Memory

By Paper With Video

Community Score: 50% | 104 views | 1y

0 community ratings: null thumbs up, null thumbs down

This video was created using https://paperspeech.com. If you’d like to create explainer videos for your own papers, please visit the website! Title: Agent Workflow Memory Authors: Zora Zhiruo Wang, Jiayuan Mao, Daniel Fried, Graham Neubig Abstract: Despite the potential of language model-based agents to solve real-world tasks such as web navigation, current methods still struggle with long-horizon tasks with complex action trajectories. In contrast, humans can flexibly solve complex tasks by learning reusable task workflows from past experiences and using them to guide future actions. To build agents that can similarly benefit from this process, we introduce Agent Workflow Memory (AWM), a method for inducing commonly reused routines, i.e., workflows, and selectively providing workflows to the agent to guide subsequent generations. AWM flexibly applies to both offline and online scenarios, where agents induce workflows from training examples beforehand or from test queries on the fly