# Improving Iterative Text Revision by Learning Where to Edit from Other Revision Tasks arXiv: https://arxiv.org/abs/2212.01350 ยท HTML: https://mlsanity.com/paper/2212.01350/ ## Key facts - Cited by 20 papers in the map (data through 14 Oct 2026). - Builds on 23 of its 41 references that are in the map. - First posted on arXiv 2 Dec 2022. ## Builds on (most cited first, 23 of 23) - [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017) - [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019) - [RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models](https://mlsanity.com/paper/2009.11462/) (2020) - [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://mlsanity.com/paper/1912.08777/) (2019) - [On Faithfulness and Factuality in Abstractive Summarization](https://mlsanity.com/paper/2005.00661/) (2020) - [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) - [GECToR -- Grammatical Error Correction: Tag, Not Rewrite](https://mlsanity.com/paper/2005.12592/) (2020) - [Sentence Simplification with Deep Reinforcement Learning](https://mlsanity.com/paper/1703.10931/) (2017) - [Encode, Tag, Realize: High-Precision Text Editing](https://mlsanity.com/paper/1909.01187/) (2019) - [Parallel Iterative Edit Models for Local Sequence Transduction](https://mlsanity.com/paper/1910.02893/) (2019) - [Politeness Transfer: A Tag and Generate Approach](https://mlsanity.com/paper/2004.14257/) (2020) - [EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing](https://mlsanity.com/paper/1906.08104/) (2019) - [Felix: Flexible Text Editing Through Tagging and Insertion](https://mlsanity.com/paper/2003.10687/) (2020) - [Seq2Edits: Sequence Transduction Using Span-level Edit Operations](https://mlsanity.com/paper/2009.11136/) (2020) - [Understanding Iterative Revision from Human-Written Text](https://mlsanity.com/paper/2203.03802/) (2022) - [Read, Revise, Repeat: A System Demonstration for Human-in-the-loop Iterative Text Revision](https://mlsanity.com/paper/2204.03685/) (2022) - [LEWIS: Levenshtein Editing for Unsupervised Text Style Transfer](https://mlsanity.com/paper/2105.08206/) (2021) - [Iterative Edit-Based Unsupervised Sentence Simplification](https://mlsanity.com/paper/2006.09639/) (2020) - [DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion](https://mlsanity.com/paper/1902.10526/) (2019) - [Text Simplification by Tagging](https://mlsanity.com/paper/2103.05070/) (2021) - [Split and Rephrase](https://mlsanity.com/paper/1707.06971/) (2017) - [Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction](https://mlsanity.com/paper/2010.03260/) (2020) - [Text Revision by On-the-Fly Representation Optimization](https://mlsanity.com/paper/2204.07359/) (2022) ## Built on by (most cited first, 20 of 20) - [A Design Space for Intelligent and Interactive Writing Assistants](https://mlsanity.com/paper/2403.14117/) (2024) - [Aligning LLM Agents by Learning Latent Preference from User Edits](https://mlsanity.com/paper/2404.15269/) (2024) - [CoEdIT: Text Editing by Task-Specific Instruction Tuning](https://mlsanity.com/paper/2305.09857/) (2023) - [Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Edits](https://mlsanity.com/paper/2409.14509/) (2024) - [ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews](https://mlsanity.com/paper/2306.12587/) (2023) - [Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance](https://mlsanity.com/paper/2305.13225/) (2023) - [mEdIT: Multilingual Text Editing via Instruction Tuning](https://mlsanity.com/paper/2402.16472/) (2024) - [Authorship Style Transfer with Policy Optimization](https://mlsanity.com/paper/2403.08043/) (2024) - [Help Me Write a Story: Evaluating LLMs' Ability to Generate Writing Feedback](https://mlsanity.com/paper/2507.16007/) (2025) - [ScholaWrite: A Dataset of End-to-End Scholarly Writing Process](https://mlsanity.com/paper/2502.02904/) (2025) - [Identifying Reliable Evaluation Metrics for Scientific Text Revision](https://mlsanity.com/paper/2506.04772/) (2025) - [Writing Assistants Should Model Social Factors of Language](https://mlsanity.com/paper/2303.16275/) (2023) - [Audio Description Generation in the Era of LLMs and VLMs: A Review of Transferable Generative AI Technologies](https://mlsanity.com/paper/2410.08860/) (2024) - [Automatic and Human-AI Interactive Text Generation](https://mlsanity.com/paper/2310.03878/) (2023) - [Style Transfer with Multi-iteration Preference Optimization](https://mlsanity.com/paper/2406.11581/) (2024) - [Patent-CR: A Dataset for Patent Claim Revision](https://mlsanity.com/paper/2412.02549/) (2024) - [G-SPEED: General SParse Efficient Editing MoDel](https://mlsanity.com/paper/2310.10480/) (2023) - [Speakerly: A Voice-based Writing Assistant for Text Composition](https://mlsanity.com/paper/2310.16251/) (2023) - [The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation](https://mlsanity.com/paper/2609.14677/) (2026) - [SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RL](https://mlsanity.com/paper/2610.02023/) (2026) ## Abstract (arXiv) Iterative text revision improves text quality by fixing grammatical errors, rephrasing for better readability or contextual appropriateness, or reorganizing sentence structures throughout a document. Most recent research has focused on understanding and classifying different types of edits in the iterative revision process from human-written text instead of building accurate and robust systems for iterative text revision. In this work, we aim to build an end-to-end text revision system that can iteratively generate helpful edits by explicitly detecting editable spans (where-to-edit) with their corresponding edit intents and then instructing a revision model to revise the detected edit spans. Leveraging datasets from other related text editing NLP tasks, combined with the specification of editable spans, leads our system to more accurately model the process of iterative text refinement, as evidenced by empirical results and human evaluations. Our system significantly outperforms previous baselines on our text revision tasks and other standard text revision tasks, including grammatical error correction, text simplification, sentence fusion, and style transfer. Through extensive qualitative and quantitative analysis, we make vital connections between edit intentions and writing quality, and better computational modeling of iterative text revisions.