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orionweller/LIMIT

LIMIT A retrieval dataset that exposes fundamental theoretical limitations of embedding-based retrieval models. Despite using simple queries like "Who likes Apples?", state-of-the-art embedding models achieve less than 20% recall@100 on LIMIT full and cannot solve LIMIT-small (46 docs). Links Paper: On the Theoretical Limitations of Embedding-Based Retrieval Code: github.com/google-deepmind/limit Full version: LIMIT (50k documents) Small version: LIMIT-small (46… See the full description on the dataset page: https://huggingface.co/datasets/orionweller/LIMIT.

Author / organizationorionweller
License (as declared)cc-by-4.0
Downloads350 (as reported by Hugging Face)
Likes10
Created28 August 2025
Last updated at source4 September 2025
retrievalembeddingsbenchmark
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