alphaXiv - Understand Research Papers
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The official browser extension for alphaXiv.
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Stable signalFree or hybridMedium-risk permissions
AI Code Finder, Alerts, Ask Questions about Papers: CatalyzeX
🧑💻 Get code for AI & other research papers, create alerts, ask authors questions directly on Google, ArXiv, Scholar, PubMed, IEEE
Users50KCurrent public install base
Rating4.8Store average score
Reviews66Public review volume
Manifest versionV3Extension platform version
7-day growth0Net users gained this week
7-day growth rate0%Relative weekly velocity
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6 assetsAI Code Finder, Alerts, Ask Questions about Papers: CatalyzeX Media preview
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4.76
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2026年7月13日2026年7月19日
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Version0.0.0.122
ManifestV3
Size345KiB
Languages1English
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English
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CatalyzeX's free browser extension instantly finds and shows open-source code implementations for any research papers (AI and more) you encounter when browsing Google, ArXiv, Scholar, Github, Twitter/X, and many other search engines, forums, LLM/AI chats, and scholarly/academic websites.
Don't see it on a website you want? Send us a note [email protected]
Code for Papers Everywhere:
▶ Browse the web as usual and you'll start seeing [CODE] buttons next to papers everywhere.
▶ These buttons will automatically appear directly on the page for any implementation links found.
▶ Click on any [CODE] button to instantly jump to the open-source implementation and explore!
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Store average score4.8Chrome Web Store aggregate rating, including ratings without synced review text
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Reviews with text50Synced review bodies
Total ratings / reviews66Chrome Web Store public rating/review count
Store average score: 4.8. The bars below are calculated from synced review text only, so they may be empty for extensions that have public ratings but no synced comments yet.
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CatalyseX – Kurzreview CatalyseX ist ein unverzichtbares Tool für alle, die im Bereich Künstliche Intelligenz und Data Science arbeiten. Es schlägt die Brücke zwischen grauer Theorie (Papers) und echter Anwendung (Code). Warum es sich lohnt: Direkt-Links zu Code: Die Extension erkennt wissenschaftliche Papers (z. B. auf arXiv, Google Scholar oder Twitter) und blendet sofort einen Button zum passenden GitHub-Repository ein. Massive Zeitersparnis: Die mühsame Suche nach der richtigen Implementierung eines Algorithmus entfällt komplett. Hervorragende Integration: Es läuft dezent im Hintergrund und taucht nur dort auf, wo es gebraucht wird. Was man beachten sollte: Inoffizieller Code: Manchmal verlinkt das Tool auf Implementierungen von Drittanbietern statt auf den Originalcode der Autoren. Ein kurzer Blick auf die GitHub-Sterne ist hier ratsam. Fokus: Es ist sehr spezifisch auf Deep Learning und KI ausgerichtet; für andere wissenschaftliche Bereiche bietet es kaum Mehrwert. Fazit: Für ML-Entwickler und Forscher ein absolutes Must-have. Wenn du mit "egg" meintest, dass es "echt gut" ist – volle Zustimmung! Es macht die Arbeit mit Forschungsarbeiten deutlich effizienter.
Merci! Votre aide m'a été très précieuse pour créer des choses qui n'existaient pas avant. Il ne me suffit que de trouver le bon mot et vous trouvez le bon papier. Continuez votre excellent travail dans un monde de théorie relative; ca prend des gens qui comprennent que le chaos est juste une facon différente de classer les choses! lol
非常好
帮大忙了！
so good!
这个怎么使用啊 ，还不会用
Amazing
非常好而且很实用 希望多多扩展应用，再多包含论文代码
超级好用
unparalleled tool for the ai revolution