Papers with Code is a platform that connects machine learning research papers with their associated code implementations. It helps researchers and developers discover state-of-the-art ML methods with working code, making AI research more accessible and reproducible.
Enables real-time tracking of AI/LLM research progress by searching and aggregating content from arXiv, GitHub, Hugging Face, and Papers with Code. Supports intelligent search, automated daily/weekly research summaries, and covers 15+ AI research areas with smart caching.
Last updated
8
MIT
Why this server?
Fetches trending ML/AI research papers from Papers with Code.
An academic paper management tool that enables multi-source research searching, batch PDF analysis, and the generation of comprehensive, cross-literature reviews. It features intelligent token compression and quality evaluation to streamline the literature review workflow for researchers.
Last updated
14
23
MIT
Why this server?
Allows searching Papers with Code for machine learning papers with code implementations.
Provides tools for discovering machine learning papers, searching tasks, datasets, methods, and repositories, browsing SOTA benchmarks and leaderboards, and mapping papers to their benchmark results.
Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.
