license:cc-by-nc-4.0 region:us
Query-document vectors and clicks for the Baidu Unbiased Learning to Rank dataset used
at the WSDM23 cup. This dataset uses the winning BERT cross-encoder from Tencent
to compute query-document vectors (768 dims), mainly for ease of use and to enable
usage of simpler, smaller neural networks that are more common in ULTR research.

This dataset contains features for part-00000.gz of the Baidu dataset,
containing 589,824 queries and 6,271,536 documents.
@InProceedings{huggingface:dataset,
    title = {baidu-ultr-590k},
    author={Philipp Hager},
    year={2023}
}
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license: cc-by-nc-4.0
---
