# StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commands

arXiv: https://arxiv.org/abs/2103.13439 · HTML: https://mlsanity.com/paper/2103.13439/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 34 references that are in the map.
- First posted on arXiv 24 Mar 2021.

## Builds on (most cited first, 14 of 14)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Sequence to Sequence Learning with Neural Networks](https://mlsanity.com/paper/1409.3215/) (2014)
- [Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer](https://mlsanity.com/paper/1803.06535/) (2018)
- [Reformulating Unsupervised Style Transfer as Paraphrase Generation](https://mlsanity.com/paper/2010.05700/) (2020)
- [Style Transfer in Text: Exploration and Evaluation](https://mlsanity.com/paper/1711.06861/) (2017)
- [Generating Sentences from Disentangled Syntactic and Semantic Spaces](https://mlsanity.com/paper/1907.05789/) (2019)
- [Shakespearizing Modern Language Using Copy-Enriched Sequence-to-Sequence Models](https://mlsanity.com/paper/1707.01161/) (2017)
- [Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer](https://mlsanity.com/paper/1805.07685/) (2018)
- [Content preserving text generation with attribute controls](https://mlsanity.com/paper/1811.01135/) (2018)
- [Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric](https://mlsanity.com/paper/2004.05001/) (2020)
- [Structured Content Preservation for Unsupervised Text Style Transfer](https://mlsanity.com/paper/1810.06526/) (2018)
- [The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation](https://mlsanity.com/paper/1910.03747/) (2019)
- [Generating Classical Chinese Poems from Vernacular Chinese](https://mlsanity.com/paper/1909.00279/) (2019)
- [Machines Getting with the Program: Understanding Intent Arguments of Non-Canonical Directives](https://mlsanity.com/paper/1912.00342/) (2019)

## Built on by (most cited first, 5 of 5)

- [End-to-End Speech-to-Text Translation: A Survey](https://mlsanity.com/paper/2312.01053/) (2023)
- [Kosp2e: Korean Speech to English Translation Corpus](https://mlsanity.com/paper/2107.02875/) (2021)
- [A Survey on Awesome Korean NLP Datasets](https://mlsanity.com/paper/2112.01624/) (2021)
- [DaG LLM ver 1.0: Pioneering Instruction-Tuned Language Modeling for Korean NLP](https://mlsanity.com/paper/2311.13784/) (2023)
- [KIT-19: A Comprehensive Korean Instruction Toolkit on 19 Tasks for Fine-Tuning Korean Large Language Models](https://mlsanity.com/paper/2403.16444/) (2024)

## Abstract (arXiv)

Paraphrasing is often performed with less concern for controlled style conversion. Especially for questions and commands, style-variant paraphrasing can be crucial in tone and manner, which also matters with industrial applications such as dialog systems. In this paper, we attack this issue with a corpus construction scheme that simultaneously considers the core content and style of directives, namely intent and formality, for the Korean language. Utilizing manually generated natural language queries on six daily topics, we expand the corpus to formal and informal sentences by human rewriting and transferring. We verify the validity and industrial applicability of our approach by checking the adequate classification and inference performance that fit with conventional fine-tuning approaches, at the same time proposing a supervised formality transfer task.