---
license: gpl-3.0
---

# TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space

> [Shaolei Zhang](https://zhangshaolei1998.github.io/), [Tian Yu](https://tianyu0313.github.io/), [Yang Feng](https://people.ucas.edu.cn/~yangfeng?language=en)*

TruthX models for paper "[TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space](https://arxiv.org/pdf/2402.17811.pdf)".

**TruthX** is an inference-time method to elicit the truthfulness of LLMs by editing their internal representations in truthful space, thereby mitigating the hallucinations of LLMs. On the [TruthfulQA benchmark](https://paperswithcode.com/sota/question-answering-on-truthfulqa), TruthX yields an average **enhancement of 20% in truthfulness** across 13 advanced LLMs.

<div  align="center">   
  <img src="./truthx_results.png" alt="img" width="100%" />
</div>
<p align="center">
  TruthfulQA MC1 accuracy of TruthX across 13 advanced LLMs
</p>


This repo provides TruthX models trained on a variety of LLMs:
- Llama-1-7B, Alpaca-7B
- Llama-2-7B, Llama-2-7B-Chat, Vicuna-7B-v1.5
- Mistral-7B-v0.1, Mistral-7B-Instruct-v0.1, Mistral-7B-Instruct-v0.2
- Baichuan2-7B-Base, Baichuan2-7B-Chat
- Chatglm3-6B-Base, Chatglm3-6B

Please refer to [GitHub repo](https://github.com/ictnlp/TruthX) and [our paper](https://arxiv.org/pdf/2402.17811.pdf) for more details.

## Licence
Model weights and the inference code are released under The GNU General Public License v3.0 (GPLv3)

## Citation

If this repository is useful for you, please cite as:

```
@misc{zhang2024truthx,
      title={TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space}, 
      author={Shaolei Zhang and Tian Yu and Yang Feng},
      year={2024},
      eprint={2402.17811},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.17811}
}
```

If you have any questions, feel free to contact `zhangshaolei20z@ict.ac.cn`.