- arXiv Bibliographic Findr
- Tech Insight: Developed in collaboration with Matt Bierbaum from Cornell Computing and Information Science, this tool offers a dynamic way to explore the citation network of arXiv papers. It’s designed for seamless navigation through an article’s citation tree, enhancing the discovery of relevant research.
- ar5iv
- Tech Specs: A collaboration with Michael Kohlhase and Deyan Ginev from Friedrich-Alexander Universität, Bruce Miller from NIST, and Ben Firschman from arXiv-Vanity. This project focuses on enhancing the usability and accessibility of arXiv papers by converting them into HTML format, a step towards improved readability and wider accessibility.
- CORE Recommender
- Behind the Scenes: Working with the CORE Team, this feature recommends relevant open access papers from a global network, including over 10,000 data providers. It’s a sophisticated aggregation tool that connects users with a vast array of research papers, right from the arXiv interface.
- arXiv Links to Code & Data
- Tech Details: In partnership with Robert Stojnic, Viktor Kerkez, and Ludovic Viaud from Papers with Code/Meta AI Research, this project provides a streamlined way to find relevant code for a paper. It leverages the extensive database of Papers with Code, linking papers to code and results in Machine Learning.
- Connected Papers
- Tech Framework: Developed by Alex Eitan Tarnavsky and team from Connected Papers, this unique tool offers a visual method to explore papers relevant to a specific field. It’s an innovative way to map out academic landscapes, create bibliographies, or just navigate the world of academic papers.
- Litmaps
- Tech Angle: Collaborating with Kyle Webster and the Litmaps team, this tool integrates interactive citation maps and modern search capabilities to offer a comprehensive research discovery experience. It allows users to visualize and navigate the citation network surrounding an arXiv article.
- Hugging Face Spaces
- Tech Implementation: This collaboration with Abubakar Abid and the Hugging Face team brings interactive applications and model demos directly into the arXiv framework. Leveraging open-source tools like Gradio and Streamlit, it allows users to experiment with models and datasets in an accessible, code-free environment.
- IArxiv
- Technical Process: Developed by Ezequiel Alvarez and the Easytech team, IArxiv uses an unsupervised Machine Learning algorithm, LDA, to tailor paper recommendations according to user preferences. It evolves to fit the reader’s interests, providing a personalized arXiv experience.
- Scite Smart
- Technical Insight: A collaboration with Josh Nicholson and Domenic Rosati, this platform enhances the process of discovering and evaluating scientific articles. It introduces Smart Citations, providing context and classification for each citation within a publication.
- ScienceCast
- Tech Overview: In partnership with Andrew Jiranek and ScienceCast, Inc., this project connects arXiv papers to interactive video and audio presentations, including AI-generated summaries, broadening the dissemination of scientific findings.
- Replicate
- Tech Dynamics: Working with Ben Firshman and team, Replicate streamlines the process of associating machine learning models with arXiv papers, making these models more accessible and user-friendly.
- Influence Flower
- Technical Architecture: Developed by Minjeong Shin and Lexing Xie, this tool visualizes citation influences among academic entities, offering a unique perspective on the impact and connections of research works.
- DagsHub
- Tech Focus: A collaboration with Dean Pleban and the DagsHub Team, this platform serves as a central hub for hosting, discovering, and collaborating on research projects, emphasizing full and reproducible implementations of arXiv
Creating a comprehensive how-to guide for each of the arXiv Labs projects requires detailed instructions on how to use these tools effectively. Let’s break down each project into a simple, step-by-step guide:
Thank you for reading this post, don’t forget to subscribe!1. How to Use arXiv Bibliographic Findr
- Access the Tool: Visit the arXiv Bibliographic Findr page.
- Search for Papers: Enter the title or arXiv ID of the paper you’re interested in.
- Find Citations: View the citation tree to see which papers have cited or are cited by the selected article.
- Navigate Through Research: Use the user-friendly interface to explore related research and contextual information.
2. How to Use ar5iv
- Find a Paper: Go to arXiv and select a paper of interest.
- Access ar5iv Version: Look for the ar5iv link on the arXiv page.
- Read in HTML: Enjoy the enhanced readability and accessibility of the HTML-formatted paper.
3. How to Use CORE Recommender
- Browse arXiv: While reading a paper on arXiv, notice the CORE Recommender sidebar.
- Find Recommendations: Click on suggested papers to discover related research.
- Access Diverse Sources: Benefit from the wide range of open access papers recommended from the global network.
4. How to Use arXiv Links to Code & Data
- Select a Paper: Find a machine learning paper on arXiv.
- Check for Code Links: Look for the ‘Links to Code’ section in the paper’s abstract page.
- Find Relevant Code: Click on the links to access code repositories and datasets related to the paper.
5. How to Use Connected Papers
- Start with a Paper: Choose an arXiv paper as your starting point.
- Access Connected Papers: Use the provided link on the arXiv page to open the Connected Papers tool.
- Visualize Connections: Find the graphical representation of related papers.
- Deep Dive into Research: Use the tool to discover prior and derivative works in a visual and interactive way.
6. How to Use Litmaps
- Access Litmaps from arXiv: Find the Litmaps link on an arXiv abstract page.
- Create a Literature Map: Use the arXiv article to build a citation map.
- Browse and Analyze: Find the top connected articles and the broader citation network.
7. How to Use Hugging Face Spaces
- Find Demos: On the arXiv page, go to the Demos tab for computer science, statistics, or electrical engineering papers.
- Find Spaces: Click on links to open-source demos in Hugging Face Spaces.
- Interact with Models: Use the interactive applications to experiment with models and datasets.
8. How to Use IArxiv
- Sign Up for IArxiv: Register on the IArxiv website.
- Set Preferences: Let the system learn your preferences by selecting categories or providing information about your past publications.
- Receive Tailored Recommendations: Check your email for daily arXiv papers sorted by AI according to your interests.
9. How to Use Scite Smart
- Access Scite from arXiv: Look for the Scite Smart link on the arXiv abstract page.
- View Smart Citations: See how the publication has been cited, with context and classification.
- Evaluate Citations: Use the information to assess the impact and relevance of the citations.
10. How to Use ScienceCast
- Find a Paper on arXiv: Choose a paper of interest.
- Access ScienceCast: Click on the ScienceCast link associated with the paper.
- Find Multimedia Content: Watch interactive video and audio presentations related to the paper.
11. How to Use Replicate
- Find a Machine Learning Paper: Select a relevant paper on arXiv.
- Look for Replicate Links: Check for links to associated machine learning models.
- Test Models: Use the provided interfaces to experiment with the paper’s models in a user-friendly way.
12. How to Use Influence Flower
- Access Influence Flower: Find the link on arXiv or visit the Influence Flower website.
- Visualize Citation Influences: Enter a paper, author, institution, or research topic to see its citation influence visualized.
13. How to Use DagsHub
- Visit DagsHub: Access the DagsHub platform.
- Find arXiv Projects: Search for projects related to arXiv papers.
- Collaborate and Find: Discover full implementations of research papers and collaborate on projects.
These guides are designed to be straightforward and user-friendly, making it easy for researchers and developers to leverage the full potential of each arXiv Labs project.
Showcase of Collaborative Projects at arXiv Labs
arXiv Bibliographic Findr
Tech Insight: This tool, developed in collaboration with Matt Bierbaum from Cornell Computing and Information Science, offers a dynamic way to explore the citation network of arXiv papers. It enables seamless navigation through an article’s citation tree, enhancing the discovery of relevant research.
ar5iv
Tech Specs: A collaboration with Michael Kohlhase and Deyan Ginev from Friedrich-Alexander Universität, Bruce Miller from NIST, and Ben Firschman from arXiv-Vanity, this project aims to enhance the usability and accessibility of arXiv papers by converting them into HTML format, improving readability and accessibility.
CORE Recommender
Behind the Scenes: Working with the CORE Team, this feature recommends relevant open access papers from a global network, including over 10,000 data providers. It’s a sophisticated aggregation tool that connects users with a vast array of research papers, right from the arXiv interface.
arXiv Links to Code & Data
Tech Details: In partnership with Robert Stojnic, Viktor Kerkez, and Ludovic Viaud from Papers with Code/Meta AI Research, this project provides a streamlined way to find relevant code for a paper. It leverages the extensive database of Papers with Code, linking papers to code and results in Machine Learning.
Connected Papers
Tech Framework: Developed by Alex Eitan Tarnavsky and team from Connected Papers, this unique tool offers a visual method to explore papers relevant to a specific field. It’s an innovative way to map out academic landscapes, create bibliographies, or navigate the world of academic papers.
Litmaps
Tech Angle: Collaborating with Kyle Webster and the Litmaps team, this tool integrates interactive citation maps and modern search capabilities to offer a comprehensive research discovery experience. It allows users to visualize and navigate the citation network surrounding an arXiv article.
Hugging Face Spaces
Tech Implementation: This collaboration with Abubakar Abid and the Hugging Face team brings interactive applications and model demos directly into the arXiv framework. It allows users to experiment with models and datasets in an accessible, code-free environment.
IArxiv
Technical Process: Developed by Ezequiel Alvarez and the Easytech team, IArxiv uses an unsupervised Machine Learning algorithm, LDA, to tailor paper recommendations according to user preferences. It evolves to fit the reader’s interests, providing a personalized arXiv experience.
Scite Smart
Technical Insight: A collaboration with Josh Nicholson and Domenic Rosati, this platform enhances the process of discovering and evaluating scientific articles. It introduces Smart Citations, providing context and classification for each citation within a publication.
ScienceCast
Tech Overview: In partnership with Andrew Jiranek and ScienceCast, Inc., this project connects arXiv papers to interactive video and audio presentations, including AI-generated summaries, broadening the dissemination of scientific findings.
Replicate
Tech Dynamics: Working with Ben Firshman and team, Replicate streamlines the process of associating machine learning models with arXiv papers, making these models more accessible and user-friendly.
Influence Flower
Technical Architecture: Developed by Minjeong Shin and Lexing Xie, this tool visualizes citation influences among academic entities, offering a unique perspective on the impact and connections of research works.
DagsHub
Tech Focus: A collaboration with Dean Pleban and the DagsHub Team, this platform serves as a central hub for hosting, discovering, and collaborating on research projects, emphasizing full and reproducible implementations of arXiv
Creating a comprehensive how-to guide for each of the arXiv Labs projects requires detailed instructions on how to use these tools effectively. Let’s break down each project into a simple, step-by-step guide:
1. How to Use arXiv Bibliographic Findr
- Access the Tool: Visit the arXiv Bibliographic Findr page.
- Search for Papers: Enter the title or arXiv ID of the paper you’re interested in.
- Find Citations: View the citation tree to see which papers have cited or are cited by the selected article.
- Navigate Through Research: Use the user-friendly interface to explore related research and contextual information.
2. How to Use ar5iv
- Find a Paper: Go to arXiv and select a paper of interest.
- Access ar5iv Version: Look for the ar5iv link on the arXiv page.
- Read in HTML: Enjoy the enhanced readability and accessibility of the HTML-formatted paper.
3. How to Use CORE Recommender
- Browse arXiv: While reading a paper on arXiv, notice the CORE Recommender sidebar.
- Find Recommendations: Click on suggested papers to discover related research.
- Access Diverse Sources: Benefit from the wide range of open access papers recommended from the global network.
4. How to Use arXiv Links to Code & Data
- Select a Paper: Find a machine learning paper on arXiv.
- Check for Code Links: Look for the ‘Links to Code’ section in the paper’s abstract page.
- Find Relevant Code: Click on the links to access code repositories and datasets related to the paper.
5. How to Use Connected Papers
- Start with a Paper: Choose an arXiv paper as your starting point.
- Access Connected Papers: Use the provided link on the arXiv page to open the Connected Papers tool.
- Visualize Connections: Find the graphical representation of related papers.
- Deep Dive into Research: Use the tool to discover prior and derivative works in a visual and interactive way.
6. How to Use Litmaps
- Access Litmaps from arXiv: Find the Litmaps link on an arXiv abstract page.
- Create a Literature Map: Use the arXiv article to build a citation map.
- Browse and Analyze: Find the top connected articles and the broader citation network.
7. How to Use Hugging Face Spaces
- Find Demos: On the arXiv page, go to the Demos tab for computer science, statistics, or electrical engineering papers.
- Find Spaces: Click on links to open-source demos in Hugging Face Spaces.
- Interact with Models: Use the interactive applications to experiment with models and datasets.
8. How to Use IArxiv
- Sign Up for IArxiv: Register on the IArxiv website.
- Set Preferences: Let the system learn your preferences by selecting categories or providing information about your past publications.
- Receive Tailored Recommendations: Check your email for daily arXiv papers sorted by AI according to your interests.
9. How to Use Scite Smart
- Access Scite from arXiv: Look for the Scite Smart link on the arXiv abstract page.
- View Smart Citations: See how the publication has been cited, with context and classification.
- Evaluate Citations: Use the information to assess the impact and relevance of the citations.
10. How to Use ScienceCast
- Find a Paper on arXiv: Choose a paper of interest.
- Access ScienceCast: Click on the ScienceCast link associated with the paper.
- Find Multimedia Content: Watch interactive video and audio presentations related to the paper.
11. How to Use Replicate
- Find a Machine Learning Paper: Select a relevant paper on arXiv.
- Look for Replicate Links: Check for links to associated machine learning models.
- Test Models: Use the provided interfaces to experiment with the paper’s models in a user-friendly way.
12. How to Use Influence Flower
- Access Influence Flower: Find the link on arXiv or visit the Influence Flower website.
- Visualize Citation Influences: Enter a paper, author, institution, or research topic to see its citation influence visualized.
13. How to Use DagsHub
- Visit DagsHub: Access the DagsHub platform.
- Find arXiv Projects: Search for projects related to arXiv papers.
- Collaborate and Find: Discover full implementations of research papers and collaborate on projects.
These guides are designed to be straightforward and user-friendly, making it easy for researchers and developers to leverage the full potential of each arXiv Labs project.
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