Papers with Code search now uses hybrid retrieval

The search system on Papers with Code integrates both keyword and semantic search, a hybrid approach that reportedly outperformed using either method on its own. The infrastructure relies on a combination of PostgreSQL with pgvector for storage and retrieval, Qwen3-Embedding-0.6B for generating text embeddings, and Hugging Face services for batch processing and serving the live model. This setup is also used to generate the related papers recommendations found on individual paper pages.

The author, who works at Hugging Face and on Papers with Code, shared this technical breakdown and invited feedback on how others are implementing hybrid search for research papers or similar technical content. The disclosure of their employment provides context for the specific tooling choices. The post focuses on the architecture and its benefits, without providing specific performance metrics or comparisons.