---
license: apache-2.0
language:
- en
base_model:
- Qwen/Qwen2.5-32B-Instruct
---
# AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials
[\[🏠Homepage\]](https://agenttrek.github.io/) [\[💻Code\]](https://github.com/xlang-ai/AgentTrek) [\[📝Paper\]](https://arxiv.org/abs/2412.09605) [\[🤗Models\]](https://huggingface.co/xlangai/AgentTrek-1.0-32B)[\[🤗Data\]]()
## Overview of Pipeline

AgentTrek is a cost-efficient and scalable framework that synthesizes high-quality agent trajectories by guiding replay with web tutorials. These collected trajectories significantly enhance agent performance.
## Quick Start
**AgentTrek-1.0-32B** is a web agent model finetuned from [Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).

- For metrics, refers to [Browsergym Leaderboard](https://huggingface.co/spaces/ServiceNow/browsergym-leaderboard)
- For evaluation, refers to [Evaluation Script](https://github.com/xlang-ai/AgentTrek)
- For training dataset, refers to [Training Dataset]()
## Citation
```bibtex
@article{xu2024agenttrek,
author = {Yiheng Xu and Dunjie Lu and Zhennan Shen and Junli Wang and Zekun Wang and Yuchen Mao and Caiming Xiong and Tao Yu},
title = {AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials},
year={2024},
eprint={2412.09605},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2412.09605}
}
```