#llm/embeddings + #leaderboard

Zero-shot retrieval quality across a heterogeneous set of IR tasks and domains, providing a common framework for comparing NLP-based retrieval models.

We’re excited to introduce the beta version of the Retrieval Embedding Benchmark (RTEB), a new benchmark designed to reliably evaluate the retrieval accuracy of embedding models for real-world applications. Existing benchmarks struggle to measure true generalization, while RTEB addresses this with a hybrid strategy of open and private datasets.