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license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- reasoning
- agent
- chain-of-thought
---
# ACTS: Agentic Chain-of-Thought Steering Controller
This repository contains a controller agent checkpoint for **ACTS (Agentic Chain-of-Thought Steering)**, presented in the paper [Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning](https://huggingface.co/papers/2606.03965).
ACTS is a framework where a lightweight controller agent adaptively steers a frozen reasoner (such as DeepSeek-R1) step-by-step under a thinking-token budget. By formulating reasoning steering as a Markov decision process, the controller chooses a reasoning strategy and a short steering phrase at each step to enable controllable accuracy–efficiency trade-offs.
## Resources
- **Paper:** [Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning](https://huggingface.co/papers/2606.03965)
- **Repository:** [Andree-9/ACTS](https://github.com/Andree-9/ACTS)
- **SFT Data:** [yuuxia/controller-sft-data](https://huggingface.co/datasets/yuuxia/controller-sft-data)
## Quick Start Inference
To use this controller to steer a reasoner, follow the setup instructions in the [GitHub repository](https://github.com/Andree-9/ACTS) and run the following command:
```bash
conda activate slime
./scripts/run_acts_inference.sh \
--controller yuuxia/acts-controller \
--reasoner deepseek-ai/DeepSeek-R1-Distill-Qwen-7B \
--benchmark aime2024 \
--budget 10000
```
## Citation
```bibtex
@misc{xia2026acts,
title={Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning},
author={Yu Xia and Zhouhang Xie and Xin Xu and Byungkyu Kang and Prarit Lamba and Xiang Gao and Julian McAuley},
year={2026},
eprint={2606.03965},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2606.03965},
}
``` |