# Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision

arXiv: https://arxiv.org/abs/2406.00197 · HTML: https://mlsanity.com/paper/2406.00197/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 31 references that are in the map.
- First posted on arXiv 31 May 2024.

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

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing](https://mlsanity.com/paper/1902.07669/) (2019)
- [Neural CRF Model for Sentence Alignment in Text Simplification](https://mlsanity.com/paper/2005.02324/) (2020)
- [NLPeer: A Unified Resource for the Computational Study of Peer Review](https://mlsanity.com/paper/2211.06651/) (2022)
- [Understanding Iterative Revision from Human-Written Text](https://mlsanity.com/paper/2203.03802/) (2022)
- [Argument Mining for Understanding Peer Reviews](https://mlsanity.com/paper/1903.10104/) (2019)
- [Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review](https://mlsanity.com/paper/2204.10805/) (2022)
- [DISAPERE: A Dataset for Discourse Structure in Peer Review Discussions](https://mlsanity.com/paper/2110.08520/) (2021)
- [ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews](https://mlsanity.com/paper/2306.12587/) (2023)
- [Does My Rebuttal Matter? Insights from a Major NLP Conference](https://mlsanity.com/paper/1903.11367/) (2019)
- [WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse](https://mlsanity.com/paper/1808.09422/) (2018)
- [HiStruct+: Improving Extractive Text Summarization with Hierarchical Structure Information](https://mlsanity.com/paper/2203.09629/) (2022)
- [arXivEdits: Understanding the Human Revision Process in Scientific Writing](https://mlsanity.com/paper/2210.15067/) (2022)
- [NewsEdits: A News Article Revision Dataset and a Document-Level Reasoning Challenge](https://mlsanity.com/paper/2206.07106/) (2022)
- [Argument Mining Driven Analysis of Peer-Reviews](https://mlsanity.com/paper/2012.07743/) (2020)
- [A Corpus of Sentence-level Revisions in Academic Writing: A Step towards Understanding Statement Strength in Communication](https://mlsanity.com/paper/1405.1439/) (2014)

## Built on by (most cited first, 11 of 11)

- [PeerQA: A Scientific Question Answering Dataset from Peer Reviews](https://mlsanity.com/paper/2502.13668/) (2025)
- [Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document Revisions](https://mlsanity.com/paper/2410.02028/) (2024)
- [Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Review](https://mlsanity.com/paper/2602.11173/) (2026)
- [Efficient Layer-wise LLM Fine-tuning for Revision Intention Prediction](https://mlsanity.com/paper/2510.00268/) (2025)
- [EarlySciRev: A Dataset of Early-Stage Scientific Revisions Extracted from LaTeX Writing Traces](https://mlsanity.com/paper/2603.28515/) (2026)
- [Zero-shot reasoning for simulating scholarly peer-review](https://mlsanity.com/paper/2510.02027/) (2025)
- [Is Peer Review Really in Decline? Analyzing Review Quality across Venues and Time](https://mlsanity.com/paper/2601.15172/) (2026)
- [Intention-Adaptive LLM Fine-Tuning for Text Revision Generation](https://mlsanity.com/paper/2602.00477/) (2026)
- [WikiSTAR: A System for Shedding Light on the Hidden History of Scientific Wikipedia Articles](https://mlsanity.com/paper/2607.12441/) (2026)
- [Heterogeneous Element-Aware Cross-Version Differencing of Scientific Documents via Layout-Aware Alignment and Structure-Aware Reasoning](https://mlsanity.com/paper/2607.14117/) (2026)
- [ReGround: Grounding Reviewer Comments in Multimodal Evidence](https://mlsanity.com/paper/2609.11460/) (2026)

## Abstract (arXiv)

Collaborative review and revision of textual documents is the core of knowledge work and a promising target for empirical analysis and NLP assistance. Yet, a holistic framework that would allow modeling complex relationships between document revisions, reviews and author responses is lacking. To address this gap, we introduce Re3, a framework for joint analysis of collaborative document revision. We instantiate this framework in the scholarly domain, and present Re3-Sci, a large corpus of aligned scientific paper revisions manually labeled according to their action and intent, and supplemented with the respective peer reviews and human-written edit summaries. We use the new data to provide first empirical insights into collaborative document revision in the academic domain, and to assess the capabilities of state-of-the-art LLMs at automating edit analysis and facilitating text-based collaboration. We make our annotation environment and protocols, the resulting data and experimental code publicly available.