How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code

How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code Published August 21, 2026 Update on GitHub Upvote 32 Niels Rogge nielsr 3 months ago, we started a revival of Papers with Code (see also the announcement tweet ). Its goal is to make open AI research accessible and digestible, so that people can easily find the artifacts related to a paper, find state-of-the-art (SOTA) across the various domains of AI, share interesting research and build on top of each other's work.

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• How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code Published August 21, 2026 Update on GitHub Upvote 32 Niels Rogge nielsr 3 months ago, we started a revival of Papers with Code (see also the announcement tweet ).
• Its goal is to make open AI research accessible and digestible, so that people can easily find the artifacts related to a paper, find state-of-the-art (SOTA) across the various domains of AI, share interesting research and build on top of each other's work.
• In other words, its goal is to power the wave of research that leads to the next Transformer .
• Of course, making AI research accessible requires a powerful search engine, so that humans and agents can quickly find relevant and related work, either through the website or the pwc search CLI command , which agents can use via the Skill .
• It's important to note that searching for research is not quite the same as searching for regular text.
• A useful paper search engine should find an exact title or arXiv identifier, but it should also understand a query such as “small language models for code generation” even when those words do not appear together in a paper.