Hugging Face Revives PapersWithCode After Meta Let It Go Unmaintained

A Beloved Resource Returns

PapersWithCode was the go-to resource for machine learning researchers: a hub connecting papers to code implementations, tracking state-of-the-art results, and maintaining benchmark leaderboards. After Meta acquired it, the site stagnated — no new papers, outdated leaderboards, and growing community frustration.

Hugging Face Steps In

Niels from Hugging Face's open-source team has launched paperswithcode.co as a community-driven revival. The new site uses AI agents to parse papers at scale and automatically generate leaderboards, currently focused on high-impact papers like Qwen 3.5/3.6, RF-DETR, DINOv3, and top embedding models from the MTEB leaderboard.

New and Improved Features

The revived site includes trending papers ranked by GitHub star velocity, domain categorization (OCR, object detection, ASR, etc.), a methods section (covering techniques like RLVR), per-benchmark leaderboards (MMTEB, COCO val2017), citation count sorting, and support for papers hosted outside arXiv.

The announcement on r/MachineLearning received 330+ upvotes, with the community expressing relief that this critical infrastructure is being maintained again — this time by an organization with strong alignment to the open-source ML ecosystem.