VibrantVista/style-judge-dataset

Style Judge Dataset

A pairwise dataset for learning a continuous style-similarity function while controlling for topic, introduced in Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning (arXiv:2512.05747).

Dataset Summary

• Total rows: 156k (default subset)
• Splits: train 130k, validation 13k, test 13k
• Format: Arrow

Columns

• sentence1 (string): original chunk text
• sentence2 (string): refilled chunk text
• score (float): calibrated similarity score in [0, 1]
• subject (string): one of 4 subject categories
• author1, author2 (string): author identifiers for each side
• book1, book2 (string): book identifiers for each side
• id1, id2 (string): example ids

Source Data (Books)

General dataset size: 978 books (strict pairs only)

Subject breakdown:

Subject	Books	Authors
Adventure stories	402	201
Historical fiction	162	81
Man-woman relationships -- Fiction	296	148
Young women -- Fiction	118	59

Loading

from datasets import load_dataset

ds = load_dataset("VibrantVista/style-judge-dataset")
train = ds["train"]
valid = ds["validation"]
test  = ds["test"]

Citation

@misc{liu2025capturingclassicauthorialstyle,
      title={Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning}, 
      author={Jinlong Liu and Mohammed Bahja and Venelin Kovatchev and Mark Lee},
      year={2025},
      eprint={2512.05747},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2512.05747}, 
}