# PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing

arXiv: https://arxiv.org/abs/2512.02589 · HTML: https://mlsanity.com/paper/2512.02589/

## Key facts

- Cited by 6 papers 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 5 of its 8 references that are in the map.
- First posted on arXiv 2 Dec 2025.

## Placed in

- LLM agents and tool use / [Web, search, and research agents](https://mlsanity.com/agents/web-search-and-research-agents/)

## Builds on (most cited first, 5 of 5)

- [Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers](https://mlsanity.com/paper/2311.09180/) (2023)
- [A Design Space for Intelligent and Interactive Writing Assistants](https://mlsanity.com/paper/2403.14117/) (2024)
- [OverleafCopilot: Empowering Academic Writing in Overleaf with Large Language Models](https://mlsanity.com/paper/2403.09733/) (2024)
- [Characterizing Stage-Aware Writing Assistance in Collaborative Document Authoring](https://mlsanity.com/paper/2008.08165/) (2020)
- [Towards AI-assisted Academic Writing](https://mlsanity.com/paper/2503.13771/) (2025)

## Built on by (most cited first, 6 of 6)

- [AI for Auto-Research: Roadmap & User Guide](https://mlsanity.com/paper/2605.18661/) (2026)
- [PaperAudit-Bench: Benchmarking Error Detection in Research Papers for Critical Automated Peer Review](https://mlsanity.com/paper/2601.19916/) (2026)
- [pAI/MSc: ML Theory Research with Humans on the Loop](https://mlsanity.com/paper/2604.20622/) (2026)
- [Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents](https://mlsanity.com/paper/2605.09915/) (2026)
- [PaperJury: Due-Process Review for Bounded LaTeX Revision](https://mlsanity.com/paper/2606.16322/) (2026)
- [DocuTeam: Mixed-Initiative Multi-Agent Discussions around Evolving Documents](https://mlsanity.com/paper/2609.29309/) (2026)

## Abstract (arXiv)

Large language models are increasingly embedded into academic writing workflows, yet existing assistants remain external to the editor, preventing deep interaction with document state, structure, and revision history. This separation makes it impossible to support agentic, context-aware operations directly within LaTeX editors such as Overleaf. We present PaperDebugger, an in-editor, multi-agent, and plugin-based academic writing assistant that brings LLM-driven reasoning directly into the writing environment. Enabling such in-editor interaction is technically non-trivial: it requires reliable bidirectional synchronization with the editor, fine-grained version control and patching, secure state management, multi-agent scheduling, and extensible communication with external tools. PaperDebugger addresses these challenges through a Chrome-approved extension, a Kubernetes-native orchestration layer, and a Model Context Protocol (MCP) toolchain that integrates literature search, reference lookup, document scoring, and revision pipelines. Our demo showcases a fully integrated workflow, including localized edits, structured reviews, parallel agent execution, and diff-based updates, encapsulated within a minimal-intrusion user interface (UI). Early aggregated analytics demonstrate active user engagement and validate the practicality of an editor-native, agentic writing assistant. More details about this demo and video could be found at https://github.com/PaperDebugger/PaperDebugger.