---
base_model:
- Qwen/Qwen3-8B
---
# EvoDS

## Model Description

This model is the backbone language model used in the paper **"EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management"**. It is initialized from **Qwen3-8B** and further trained to support autonomous data science tasks through multi-agent supervised fine-tuning and reinforcement learning.

## Base Model

* Base Model: Qwen3-8B

## About EvoDS

EvoDS is a self-evolving autonomous data science agent that continuously improves its capabilities over time. The framework introduces two key mechanisms:

### Autonomous Skill Acquisition (ASA)

ASA enables the agent to autonomously synthesize, validate, cache, and reuse executable skills, allowing the agent's action space to expand over time.

### Adaptive Context Compression (ACC)

ACC enables efficient long-horizon reasoning by dynamically compressing interaction history and preserving critical information under limited context budgets.

## Resources

* Paper: [EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management](https://arxiv.org/abs/2606.03841v1)
* Code Repository: https://github.com/usail-hkust/EvoDS

## Citation

```bibtex
@article{yang2026evods,
  title={EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management},
  author={Yang, Zherui and Liu, Fan and Ning, Yansong and Liu, Hao},
  journal={arXiv preprint arXiv:2606.03841},
  year={2026}
}
```