RongxinChen/MBTI_dpo_t_f
Multi-Personality Generation of LLMs at Decoding-time Paper | Code This repository contains the DPO (Direct Preference Optimization) datasets used in the paper "Multi-Personality Generation of LLMs at Decoding-time". The study introduces the Multi-Personality Generation (MPG) framework, a novel decoding-time paradigm that enables LLMs to simultaneously embody multiple personalization attributes without extra training. The datasets include: 🧩 MBTI Datasets These… See the full description on the dataset page: https://huggingface.co/datasets/RongxinChen/MBTI_dpo_t_f.
Multi-Personality Generation of LLMs at Decoding-time
This repository contains the DPO (Direct Preference Optimization) datasets used in the paper "Multi-Personality Generation of LLMs at Decoding-time". The study introduces the Multi-Personality Generation (MPG) framework, a novel decoding-time paradigm that enables LLMs to simultaneously embody multiple personalization attributes without extra training.
The datasets include:
🧩 MBTI Datasets
These datasets focus on specific Myers-Briggs Type Indicator dimensions:
- E / I: Extraversion vs. Introversion
- J / P: Judging vs. Perceiving
- T / F: Thinking vs. Feeling
- S / N: Sensing vs. Intuition
🎭 RolePlay Datasets
Datasets designed for enhancing role-playing capabilities:
- Personality: DPO data for general personality alignment.
- Profile: DPO data based on character profiles.
Citation
If you find our work or datasets useful, please consider citing our paper:
@inproceedings{chen2026multipersonality,
title={Multi-Personality Generation of LLMs at Decoding-time},
author={Chen, Rongxin and Li, Yunfan and Yuan, Yige and Xu, Bingbing and Shen, Huawei},
booktitle={Proceedings of the 19th ACM International Conference on Web Search and Data Mining (WSDM '26)},
year={2026},
publisher={ACM},
url={http://arxiv.org/abs/2511.01891}
}