ReBalance / README.md
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metadata
license: mit
tags:
  - rebalance
  - steering-vector
  - reasoning
  - llm
  - iclr-2026
language:
  - en

ReBalance Steering Vectors

Steering vectors for Efficient Reasoning with Balanced Thinking (ICLR 2026)

Paper (Hugging Face) Paper (Open Review) Code (GitHub) Project Page License: MIT

Overview

This repository provides steering vectors only for ReBalance.

It does not include:

  • base model weights,
  • inference/training code,
  • datasets.

Use this repository together with the official codebase:

Available Steering Vectors

Base model Vector path Recommended --steer_layer
DeepSeek-R1-Distill-Qwen-1.5B vectors/DeepSeek-R1-Distill-Qwen-1.5B/steer_vector_layer19_conf_mixed.pt 19
DeepSeek-R1-Distill-Qwen-7B vectors/DeepSeek-R1-Distill-Qwen-7B/steer_vector_layer22_conf_mixed.pt 22
QwQ-32B vectors/QwQ-32B/steer_vector_layer58_conf_mixed.pt 58

Local Directory Layout (after download)

ReBalance/
β”œβ”€β”€ transformer_inference_steer_dp.py
└── vectors/
    β”œβ”€β”€ DeepSeek-R1-Distill-Qwen-1.5B/
    β”‚   └── steer_vector_layer19_conf_mixed.pt
    β”œβ”€β”€ DeepSeek-R1-Distill-Qwen-7B/
    β”‚   └── steer_vector_layer22_conf_mixed.pt
    └── QwQ-32B/
        └── steer_vector_layer58_conf_mixed.pt

Download

Option 1: Clone the full model repository

git lfs install
git clone https://huggingface.co/Yulin-Li/ReBalance

Then copy the vectors/ folder into your local ReBalance/ root directory.

Option 2: Download only the vectors with huggingface_hub

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="Yulin-Li/ReBalance",
    repo_type="model",
    allow_patterns="vectors/*",
    local_dir="."
)

Quick Usage with ReBalance

python transformer_inference_steer_dp.py \
  --model_name_or_path 'DeepSeek-R1-Distill-Qwen-1.5B' \
  --dataset_dir "./Data/" \
  --output_path "./outputs" \
  --dataset "Math_AIME2024" \
  --max_generated_tokens 16000 \
  --num_gpus 8 \
  --steer_vector_path ./vectors/DeepSeek-R1-Distill-Qwen-1.5B/steer_vector_layer19_conf_mixed.pt \
  --steer_layer 19 \
  --steer_coef -1

Paper, Code, and Project Links

Intended Use

  • Research and reproducibility for ReBalance.
  • Experiments on reasoning efficiency and accuracy trade-offs.
  • Comparative studies on overthinking mitigation.

Citation

If you find ReBalance useful in your research, please cite our paper:

@article{li2026efficient,
  title={Efficient Reasoning with Balanced Thinking},
  author={Li, Yulin and Tu, Tengyao and Ding, Li and Wang, Junjie and Zhen, Huiling and Chen, Yixin and Li, Yong and Tian, Zhuotao},
  booktitle={Proceedings of the 14th International Conference on Learning Representations},
  year={2026}
}