Paperlib is an open-source academic paper management tool designed for researchers, particularly those in fields heavily reliant on conference papers. It addresses the difficulty of scraping metadata for conference publications, which often lack DOIs, by providing accurate metadata extraction, library organization, and seamless citation export for writing.

How It Works

Paperlib employs a robust metadata scraping engine capable of extracting information from various sources, with a focus on conference papers. It allows users to write custom scrapers, tailoring the tool to specific disciplines. The application offers full-text and advanced search capabilities, smart filtering, and supports traditional organization methods like ratings, flags, tags, and folders, alongside markdown notes.

Quick Start & Requirements

• Install: Download installers for Windows, macOS, and Linux from the official webpage.
• Prerequisites: macOS users may need to bypass security settings.
• Links: Webpage, Download, Quick Start, Roadmap

Highlighted Details

• Scrapes metadata for numerous conference papers (e.g., ICLR, ICML, NeurIPS).
• Features a macOS spotlight-like plugin for easy reference copying into editors (including MS Word).
• Supports cloud sync across macOS, Linux, and Windows.
• Extensible via user-created extensions for features like citation counts, LLM-based summarization, and semantic search.

Maintenance & Community

The project is actively seeking collaborators. A Discord community is available for discussion.

Licensing & Compatibility

• License: GPL-3.0.
• Compatibility: The GPL-3.0 license may impose copyleft restrictions on derivative works or linking within closed-source projects.

Limitations & Caveats

Windows installers may trigger security warnings due to the lack of code signing, requiring manual user override. The project is seeking additional developers to aid in its ongoing development.