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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.

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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 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:

bibtex
@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}
}