README.md

🎭 Atomic Persona Evaluation

Official code & data for “Spotting Out-of-Character Behavior: Atomic-Level Evaluation of Persona Fidelity in Open-Ended Generation” (Findings of ACL 2025). [arXiv] [ACL Anthology]
We introduce ACC_atom, IC_atom, and RC_atom – three complementary metrics that diagnose how well a generated response respects each atomic persona statement rather than a coarse, one-shot persona summary.

Overview

This project provides persona assignment and evaluation prompts to assess how well persona fragments—LLM-generated statements containing a specific character—match a target persona. Leveraging principles from atomic design and prompt engineering, the toolkit helps developers analyze and refine persona content systematically using LLM APIs (e.g., GPT).

Installation

1. Clone this repo

git clone https://github.com/ddindidu/atomic-persona-evaluation.git
cd atomic-persona-evaluation

2. Install dependencies (Conda)

conda env create -f env.yml          # creates env "atomeval"
conda activate atomeval

Usage

1. Generate persona statements

(will be uploaded soon!)

2. Run Evaluation

(will be uploaded soon!)

Reference

Cite our work with the following format:

@inproceedings{shin-etal-2025-spotting,
    title = "Spotting Out-of-Character Behavior: Atomic-Level Evaluation of Persona Fidelity in Open-Ended Generation",
    author = "Shin, Jisu  and
      Oh, Juhyun  and
      Kim, Eunsu  and
      Song, Hoyun  and
      Oh, Alice",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.findings-acl.1349/",
    pages = "26312--26332",
    ISBN = "979-8-89176-256-5",
}