PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers on Overleaf
On the map: LLM agents and tool use → Web, search, and research agents
Abstract (arXiv)
Expert writing feedback from experienced researchers is critical for early-career scholars to improve their manuscripts, yet high-quality feedback often remains scarce because reviewing research papers is labor-intensive. Emerging AI-powered writing assistants largely focus on grammar fixes or simulating peer review with final scores, yet they fall short of providing concrete, actionable suggestions that help students improve their papers during drafting. We present PaperMentor, a human-centered writing assistant system that delivers actionable suggestions as Overleaf-native inline comments while leaving the actual writing entirely to human authors. PaperMentor integrates an expert skill library carefully curated from established researchers' writing advice with 12 specialized agents covering different aspects of paper writing, such as formatting compliance, phrasing accuracy, and terminology consistency. In a user study (n=14), 90.6% of the generated comments were rated actionable and 67.5% were rated valid, significantly outperforming a GPT-5.2 baseline uswithout the skill library. We release PaperMentor as open source for public use. Our code is publicly available under the AGPL-3.0 license at https://github.com/jiarui-liu/overleaf
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 13 of its 40 references that are in the map. First posted on arXiv 7 Jun 2026.
Builds on
13 of 40 references.
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Other references · 12
- 2018Datasheets for Datasetscited by 1,386
- 2023Can large language models provide useful feedback on research papers? A large-scale empirical analysiscited by 200
- 2023ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewingcited by 122
- 2025DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking Processcited by 100
- 2024A Design Space for Intelligent and Interactive Writing Assistantscited by 76
- 2025Large language models for automated scholarly paper review: A surveycited by 61
- 2024Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Modelscited by 51
- 2025Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025cited by 47
- 2024Automated Focused Feedback Generation for Scientific Writing Assistancecited by 33
- 2020What Can We Do to Improve Peer Review in NLP?cited by 32
- 2025ReviewAgents: Bridging the Gap Between Human and AI-Generated Paper Reviewscited by 32
- 2023LLM-as-a-tutor in EFL Writing Education: Focusing on Evaluation of Student-LLM Interactioncited by 29
Built on by
Citing papers per year: 2026: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2026Prober.ai: Gated Inquiry-Based Feedback via LLM-Constrained Personas for Argumentative Writing Development
- 2026PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress
- 2025AISSISTANT: Human-AI Collaborative Review and Perspective Research Workflows in Data Science
- 2025Writing as a testbed for open ended agents
- 2026Towards Automating Scientific Review with Google's Paper Assistant Tool
- 2026PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement
- 2025Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents
- 2025PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing