# BiSECT: Learning to Split and Rephrase Sentences with Bitexts

arXiv: https://arxiv.org/abs/2109.05006 · HTML: https://mlsanity.com/paper/2109.05006/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 37 references that are in the map.
- First posted on arXiv 10 Sep 2021.

## Builds on (most cited first, 18 of 18)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [Get To The Point: Summarization with Pointer-Generator Networks](https://mlsanity.com/paper/1704.04368/) (2017)
- [Six Challenges for Neural Machine Translation](https://mlsanity.com/paper/1706.03872/) (2017)
- [Leveraging Pre-trained Checkpoints for Sequence Generation Tasks](https://mlsanity.com/paper/1907.12461/) (2019)
- [GECToR -- Grammatical Error Correction: Tag, Not Rewrite](https://mlsanity.com/paper/2005.12592/) (2020)
- [BLEU is Not Suitable for the Evaluation of Text Simplification](https://mlsanity.com/paper/1810.05995/) (2018)
- [Controllable Text Simplification with Explicit Paraphrasing](https://mlsanity.com/paper/2010.11004/) (2020)
- [ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations](https://mlsanity.com/paper/1711.05732/) (2017)
- [Learning To Split and Rephrase From Wikipedia Edit History](https://mlsanity.com/paper/1808.09468/) (2018)
- [ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translation](https://mlsanity.com/paper/1901.03644/) (2019)
- [Split and Rephrase](https://mlsanity.com/paper/1707.06971/) (2017)
- [Rethinking Automatic Evaluation in Sentence Simplification](https://mlsanity.com/paper/2104.07560/) (2021)
- [Split and Rephrase: Better Evaluation and a Stronger Baseline](https://mlsanity.com/paper/1805.01035/) (2018)
- [Transforming Complex Sentences into a Semantic Hierarchy](https://mlsanity.com/paper/1906.01038/) (2019)
- [Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation](https://mlsanity.com/paper/1409.1257/) (2014)
- [Small but Mighty: New Benchmarks for Split and Rephrase](https://mlsanity.com/paper/2009.08560/) (2020)
- [ABCD: A Graph Framework to Convert Complex Sentences to a Covering Set of Simple Sentences](https://mlsanity.com/paper/2106.12027/) (2021)

## Built on by (most cited first, 18 of 18)

- [LENS: A Learnable Evaluation Metric for Text Simplification](https://mlsanity.com/paper/2212.09739/) (2022)
- [Prompted Opinion Summarization with GPT-3.5](https://mlsanity.com/paper/2211.15914/) (2022)
- [GEMv2: Multilingual NLG Benchmarking in a Single Line of Code](https://mlsanity.com/paper/2206.11249/) (2022)
- [DEPLAIN: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification](https://mlsanity.com/paper/2305.18939/) (2023)
- [Multilingual Simplification of Medical Texts](https://mlsanity.com/paper/2305.12532/) (2023)
- [PETCI: A Parallel English Translation Dataset of Chinese Idioms](https://mlsanity.com/paper/2202.09509/) (2022)
- [Improving Large-scale Paraphrase Acquisition and Generation](https://mlsanity.com/paper/2210.03235/) (2022)
- [Rewriting the Script: Adapting Text Instructions for Voice Interaction](https://mlsanity.com/paper/2306.09992/) (2023)
- [Split and Rephrase with Large Language Models](https://mlsanity.com/paper/2312.11075/) (2023)
- [Defining and Detecting Vulnerability in Human Evaluation Guidelines: A Preliminary Study Towards Reliable NLG Evaluation](https://mlsanity.com/paper/2406.07935/) (2024)
- [Compare without Despair: Reliable Preference Evaluation with Generation Separability](https://mlsanity.com/paper/2407.01878/) (2024)
- [Semantic Graphs for Syntactic Simplification: A Revisit from the Age of LLM](https://mlsanity.com/paper/2407.04067/) (2024)
- [Sequence-to-Sequence Spanish Pre-trained Language Models](https://mlsanity.com/paper/2309.11259/) (2023)
- [WikiSplit++: Easy Data Refinement for Split and Rephrase](https://mlsanity.com/paper/2404.09002/) (2024)
- [The Fewer Splits are Better: Deconstructing Readability in Sentence Splitting](https://mlsanity.com/paper/2302.00937/) (2023)
- [CREDENCE: Claim Reduction for Decomposition & Enhanced Credibility -- Semantic Metrics and Convergence Analysis](https://mlsanity.com/paper/2606.19819/) (2026)
- [From Lengthy to Lucid: A Systematic Literature Review on NLP Techniques for Taming Long Sentences](https://mlsanity.com/paper/2312.05172/) (2023)
- [EASSE-DE: Easier Automatic Sentence Simplification Evaluation for German](https://mlsanity.com/paper/2404.03563/) (2024)

## Abstract (arXiv)

An important task in NLP applications such as sentence simplification is the ability to take a long, complex sentence and split it into shorter sentences, rephrasing as necessary. We introduce a novel dataset and a new model for this `split and rephrase' task. Our BiSECT training data consists of 1 million long English sentences paired with shorter, meaning-equivalent English sentences. We obtain these by extracting 1-2 sentence alignments in bilingual parallel corpora and then using machine translation to convert both sides of the corpus into the same language. BiSECT contains higher quality training examples than previous Split and Rephrase corpora, with sentence splits that require more significant modifications. We categorize examples in our corpus, and use these categories in a novel model that allows us to target specific regions of the input sentence to be split and edited. Moreover, we show that models trained on BiSECT can perform a wider variety of split operations and improve upon previous state-of-the-art approaches in automatic and human evaluations.