Papers with Code excels in providing researchers with access to a vast array of machine learning papers with linked code implementations, while Connected Papers offers a unique visual exploration of related academic literature. Papers with Code is noted for its user-friendly interface and collaboration tools, whereas Connected Papers is praised for its innovative graph-based visualization and performance in interdisciplinary research.
Best for
Papers with Code is the better choice when the primary focus is on accessing and applying machine learning research papers directly in development projects within a small team or solo setting.
Best for
Connected Papers is the better choice when exploring and visualizing academic research trends and connections is crucial for large-scale literature reviews in interdisciplinary fields.
Key Differences
Verdict
For researchers and developers focused on machine learning and hands-on applications, Papers with Code remains the go-to choice due to its extensive code repository and benchmark datasets. Conversely, those interested in a broader academic exploration and visual understanding of research trends will find value in Connected Papers' graph-based approach. Teams with diverse research needs could benefit from combining both tools to maximize their research and development capabilities.
Papers with Code
Your daily dose of AI research from AK
Papers with Code receives praise for its extensive catalog of machine learning research papers coupled with code implementations, making it a valuable resource for both learning and project development. Users appreciate the integration of code, which aids in practical understanding and application of theoretical work. However, a few users note that some papers lack comprehensive code examples or have discrepancies between reported and reproduced results. While it is generally seen as a free and indispensable tool for researchers and developers, there are mentions of resource constraints potentially limiting its expansiveness.
Connected Papers
A unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work.
Connected Papers is highly praised for its unique visual approach to discovering and exploring academic literature, which is beneficial for researchers and scientists. Users appreciate features like mobile support, integration with arXiv, downloads in .bib format, multi-origin graphs, and links to code implementations, which enhance research efficiency. Some users reported server performance issues during spikes in user visits, reflecting a need for infrastructure scaling. The overall sentiment around pricing is not explicitly mentioned, suggesting it may not be a significant concern compared to the tool's functionality and growing reputation in the academic community.
Papers with Code
-50% vs last weekConnected Papers
+133% vs last weekPapers with Code
Connected Papers
Papers with Code
Connected Papers
Papers with Code
Connected Papers
Papers with Code (6)
Connected Papers (6)
Shared (1)
Only in Papers with Code (7)
Only in Connected Papers (7)
Only in Papers with Code (8)
Only in Connected Papers (15)
Papers with Code
Connected Papers
Papers with Code
Connected Papers
Papers with Code
Connected Papers
Papers with Code
Connected Papers
Papers with Code
I made a Claude Code plugin that draws matplotlib figures in that soft-pastel "alignment research blog" style
You know the look — the figures in Anthropic's research posts. Bold sans-serif titles, scatter points under a smoothed trend line with a shaded band, those bars with the slightly rounded tops, little ↓better badges in the corner. I kept wanting my own plots to look like that and kept rebuilding the
Connected Papers
After a long beta, we are launching! Connected Papers is a unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work. https://t.co/KgAbUxmz
After a long beta, we are launching! Connected Papers is a unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work. https://t.co/KgAbUxmzU0
Only in Papers with Code (5)
Papers with Code is better suited for machine learning projects because it offers direct access to research papers and code implementations related to project development.
Papers with Code uses a subscription-based tiered pricing, which could be more flexible for long-term users, whereas Connected Papers offers a simpler tiered pricing which might cater better to users focusing on short-term, intensive research projects.
Both tools have robust support from academic communities, but Papers with Code benefits from integrations with platforms like GitHub and Slack, potentially offering more dynamic collaboration possibilities.
Yes, integrating both can enhance research capabilities: Papers with Code for direct application of machine learning concepts and Connected Papers for exploring broader research trends.
Connected Papers is generally easier to get started with due to its intuitive visual interface and minimal setup requirements, while Papers with Code's deeper integration features might have a steeper initial learning curve.
