# IdEALS: Idiomatic Expressions for Advancement of Language Skills

arXiv: https://arxiv.org/abs/2305.13637 · HTML: https://mlsanity.com/paper/2305.13637/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 20 of its 38 references that are in the map.
- First posted on arXiv 23 May 2023.

## Builds on (most cited first, 20 of 20)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://mlsanity.com/paper/1704.05426/) (2017)
- [A large annotated corpus for learning natural language inference](https://mlsanity.com/paper/1508.05326/) (2015)
- [Adversarial NLI: A New Benchmark for Natural Language Understanding](https://mlsanity.com/paper/1910.14599/) (2019)
- [GECToR -- Grammatical Error Correction: Tag, Not Rewrite](https://mlsanity.com/paper/2005.12592/) (2020)
- [Bilateral Multi-Perspective Matching for Natural Language Sentences](https://mlsanity.com/paper/1702.03814/) (2017)
- [Paraphrase Generation with Deep Reinforcement Learning](https://mlsanity.com/paper/1711.00279/) (2017)
- [An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction](https://mlsanity.com/paper/1909.00502/) (2019)
- [A Deep Generative Framework for Paraphrase Generation](https://mlsanity.com/paper/1709.05074/) (2017)
- [Neural Paraphrase Generation with Stacked Residual LSTM Networks](https://mlsanity.com/paper/1610.03098/) (2016)
- [A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction](https://mlsanity.com/paper/1801.08831/) (2018)
- [On the Evaluation Metrics for Paraphrase Generation](https://mlsanity.com/paper/2202.08479/) (2022)
- [EPIE Dataset: A Corpus For Possible Idiomatic Expressions](https://mlsanity.com/paper/2006.09479/) (2020)
- [Improving Grammatical Error Correction with Machine Translation Pairs](https://mlsanity.com/paper/1911.02825/) (2019)
- [Unsupervised Paraphrase Generation using Pre-trained Language Models](https://mlsanity.com/paper/2006.05477/) (2020)
- [Unsupervised Paraphrasing with Pretrained Language Models](https://mlsanity.com/paper/2010.12885/) (2020)
- [Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1](https://mlsanity.com/paper/2006.02964/) (2020)
- [D-PAGE: Diverse Paraphrase Generation](https://mlsanity.com/paper/1808.04364/) (2018)
- [SERRANT: a syntactic classifier for English Grammatical Error Types](https://mlsanity.com/paper/2104.02310/) (2021)
- [Understanding Metrics for Paraphrasing](https://mlsanity.com/paper/2205.13119/) (2022)

## Abstract (arXiv)

Although significant progress has been made in developing methods for Grammatical Error Correction (GEC), addressing word choice improvements has been notably lacking and enhancing sentence expressivity by replacing phrases with advanced expressions is an understudied aspect. In this paper, we focus on this area and present our investigation into the task of incorporating the usage of idiomatic expressions in student writing. To facilitate our study, we curate extensive training sets and expert-annotated testing sets using real-world data and evaluate various approaches and compare their performance against human experts.