license: mit
task_categories:
- other
tags: - persona-drift
- activation-steering
- mechanistic-interpretability
The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models
This repository contains pre-computed axes and persona vectors for Gemma 2 27B, Qwen 3 32B, and Llama 3.3 70B, as described in the paper The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models.
The Assistant Axis is a direction in activation space that captures how "Assistant-like" a model's current persona is. It can be used to:
- Monitor persona drift in real-time by projecting activations onto the axis.
- Steer model behavior toward or away from the default Assistant persona.
- Mitigate persona-based jailbreaks through activation capping.
Usage
You can load the pre-computed axes using the huggingface_hub library. To use the helper functions like load_axis, you should clone the official repository.
from huggingface_hub import hf_hub_download
from assistant_axis import load_model, load_axis
# Load model
model, tokenizer = load_model("google/gemma-2-27b-it")
# Download pre-computed axis
axis_path = hf_hub_download(
repo_id="lu-christina/assistant-axis-vectors",
filename="gemma-2-27b/assistant_axis.pt",
repo_type="dataset"
)
axis = load_axis(axis_path)
Citation
@misc{lu2026assistant,
title={The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models},
author={Christina Lu and Jack Gallagher and Jonathan Michala and Kyle Fish and Jack Lindsey},
year={2026},
eprint={2601.10387},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2601.10387},
}