5 items
Auto-organize arxiv papers into a local, multi-dimensional library. PaperPrism turns your arxiv PDF downloads into a searchable, auto-classified local library — without sending a single paper to the cloud. ━━━ What it does ━━━ • Watches arxiv downloads and archives each paper automatically. • Extracts title, authors, abstract, and publication date from the PDF and the arxiv API. • Classifies papers into multi-dimensional labels (topic, task, methodology, venue) using your own LLM — running on your machine or via your own API key. • Auto-generates 2–5 concise tags per paper on ingest. • Lets you batch-select papers and synthesise them into a named Topic with a one-liner summary. • Built-in Dashboard to browse, full-text search, filter by tag / topic / dimension, view PDFs inline, and bulk-import an existing folder of papers. ━━━ Privacy ━━━ All data stays on your device. PDFs live in a hidden local vault; metadata lives in a local SQLite database. The extension communicates only with your own machine (127.0.0.1). No telemetry, no analytics, no cloud sync. The optional LLM classification step calls the provider you choose, governed by that provider's own privacy policy. You can also use a fully local model to keep everything offline. ━━━ How it works ━━━ PaperPrism consists of two parts: 1. This Chrome extension — the capture layer and UI. 2. A lightweight local Agent (Python, ~15 MB installed) that handles storage and classification. Install the Agent with a single command: uv tool install paperprism-agent paperprism-agent serve Then click the PaperPrism toolbar icon and follow the 4-step setup wizard. ━━━ Open source ━━━ MIT-style Apache-2.0 license. Source: https://github.com/MrMao007/PaperPrism
May 11, 2026
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.