# Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review

arXiv: https://arxiv.org/abs/2204.10805 · HTML: https://mlsanity.com/paper/2204.10805/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- Builds on 26 of its 65 references that are in the map.
- First posted on arXiv 22 Apr 2022.

## Builds on (most cited first, 26 of 26)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [FEVER: a large-scale dataset for Fact Extraction and VERification](https://mlsanity.com/paper/1803.05355/) (2018)
- [Fact or Fiction: Verifying Scientific Claims](https://mlsanity.com/paper/2004.14974/) (2020)
- [A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers](https://mlsanity.com/paper/2105.03011/) (2021)
- [SPECTER: Document-level Representation Learning using Citation-informed Transformers](https://mlsanity.com/paper/2004.07180/) (2020)
- [Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction](https://mlsanity.com/paper/1808.09602/) (2018)
- [A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications](https://mlsanity.com/paper/1804.09635/) (2018)
- [Structural Scaffolds for Citation Intent Classification in Scientific Publications](https://mlsanity.com/paper/1904.01608/) (2019)
- [Parsing Argumentation Structures in Persuasive Essays](https://mlsanity.com/paper/1604.07370/) (2016)
- [Argumentation Mining in User-Generated Web Discourse](https://mlsanity.com/paper/1601.02403/) (2016)
- [Can We Automate Scientific Reviewing?](https://mlsanity.com/paper/2102.00176/) (2021)
- [ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis](https://mlsanity.com/paper/2010.06119/) (2020)
- [Pretrained Language Models for Sequential Sentence Classification](https://mlsanity.com/paper/1909.04054/) (2019)
- [AxCell: Automatic Extraction of Results from Machine Learning Papers](https://mlsanity.com/paper/2004.14356/) (2020)
- [Automatically Generating Commit Messages from Diffs using Neural Machine Translation](https://mlsanity.com/paper/1708.09492/) (2017)
- [Argument Mining for Understanding Peer Reviews](https://mlsanity.com/paper/1903.10104/) (2019)
- [Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols](https://mlsanity.com/paper/2009.14237/) (2020)
- [CDLM: Cross-Document Language Modeling](https://mlsanity.com/paper/2101.00406/) (2021)
- [PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space](https://mlsanity.com/paper/1909.11258/) (2019)
- [Annotation and Classification of Sentence-level Revision Improvement](https://mlsanity.com/paper/1909.05309/) (2019)
- [Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time](https://mlsanity.com/paper/2005.10865/) (2020)
- [On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks](https://mlsanity.com/paper/2010.05103/) (2020)
- [The Universal Decompositional Semantics Dataset and Decomp Toolkit](https://mlsanity.com/paper/1909.13851/) (2019)

## Built on by (most cited first, 30 of 37)

- [ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing](https://mlsanity.com/paper/2306.00622/) (2023)
- [OpenReviewer: A Specialized Large Language Model for Generating Critical Scientific Paper Reviews](https://mlsanity.com/paper/2412.11948/) (2024)
- [NLPeer: A Unified Resource for the Computational Study of Peer Review](https://mlsanity.com/paper/2211.06651/) (2022)
- [Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://mlsanity.com/paper/2502.05151/) (2025)
- [ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews](https://mlsanity.com/paper/2306.12587/) (2023)
- [Automated Focused Feedback Generation for Scientific Writing Assistance](https://mlsanity.com/paper/2405.20477/) (2024)
- [What Can Natural Language Processing Do for Peer Review?](https://mlsanity.com/paper/2405.06563/) (2024)
- [PeerQA: A Scientific Question Answering Dataset from Peer Reviews](https://mlsanity.com/paper/2502.13668/) (2025)
- [CASIMIR: A Corpus of Scientific Articles enhanced with Multiple Author-Integrated Revisions](https://mlsanity.com/paper/2403.00241/) (2024)
- [CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?](https://mlsanity.com/paper/2503.21717/) (2025)
- [Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision](https://mlsanity.com/paper/2406.00197/) (2024)
- [Attribute or Abstain: Large Language Models as Long Document Assistants](https://mlsanity.com/paper/2407.07799/) (2024)
- [Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document Revisions](https://mlsanity.com/paper/2410.02028/) (2024)
- [ScholaWrite: A Dataset of End-to-End Scholarly Writing Process](https://mlsanity.com/paper/2502.02904/) (2025)
- [Understanding Fine-grained Distortions in Reports of Scientific Findings](https://mlsanity.com/paper/2402.12431/) (2024)
- [CARE: Collaborative AI-Assisted Reading Environment](https://mlsanity.com/paper/2302.12611/) (2023)
- [NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment](https://mlsanity.com/paper/2604.11543/) (2026)
- [Document Structure in Long Document Transformers](https://mlsanity.com/paper/2401.17658/) (2024)
- [Large Language Models Penetration in Scholarly Writing and Peer Review](https://mlsanity.com/paper/2502.11193/) (2025)
- [Investigating Expert-in-the-Loop LLM Discourse Patterns for Ancient Intertextual Analysis](https://mlsanity.com/paper/2409.01882/) (2024)
- [ArgInstruct: Specialized Instruction Fine-Tuning for Computational Argumentation](https://mlsanity.com/paper/2505.22076/) (2025)
- [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)
- [Loci Similes: A Benchmark for Extracting Intertextualities in Latin Literature](https://mlsanity.com/paper/2601.07533/) (2026)
- [Multi-Agent LLMs for Generating Research Limitations](https://mlsanity.com/paper/2601.11578/) (2025)
- ['Your AI Text is not Mine': Redefining and Evaluating AI-generated Text Detection under Realistic Assumptions](https://mlsanity.com/paper/2606.04906/) (2026)
- [How Data Scientists Review the Scholarly Literature](https://mlsanity.com/paper/2301.03774/) (2023)
- [Commitment Checklist: Auditing Author Commitments in Peer Review](https://mlsanity.com/paper/2603.00003/) (2026)
- [EarlySciRev: A Dataset of Early-Stage Scientific Revisions Extracted from LaTeX Writing Traces](https://mlsanity.com/paper/2603.28515/) (2026)
- [An Inclusive Notion of Text](https://mlsanity.com/paper/2211.05604/) (2022)
- [ABCD-LINK: Annotation Bootstrapping for Cross-Document Fine-Grained Links](https://mlsanity.com/paper/2509.01387/) (2025)

## Abstract (arXiv)

Peer review is a key component of the publishing process in most fields of science. The increasing submission rates put a strain on reviewing quality and efficiency, motivating the development of applications to support the reviewing and editorial work. While existing NLP studies focus on the analysis of individual texts, editorial assistance often requires modeling interactions between pairs of texts -- yet general frameworks and datasets to support this scenario are missing. Relationships between texts are the core object of the intertextuality theory -- a family of approaches in literary studies not yet operationalized in NLP. Inspired by prior theoretical work, we propose the first intertextual model of text-based collaboration, which encompasses three major phenomena that make up a full iteration of the review-revise-and-resubmit cycle: pragmatic tagging, linking and long-document version alignment. While peer review is used across the fields of science and publication formats, existing datasets solely focus on conference-style review in computer science. Addressing this, we instantiate our proposed model in the first annotated multi-domain corpus in journal-style post-publication open peer review, and provide detailed insights into the practical aspects of intertextual annotation. Our resource is a major step towards multi-domain, fine-grained applications of NLP in editorial support for peer review, and our intertextual framework paves the path for general-purpose modeling of text-based collaboration. Our corpus and accompanying code are publicly available.