grill-lab/browsecomp-plus-indexes
Indexes of Retrievers on the Passage and Document Corpora of the BrowseComp-Plus Dataset Total downloads since release, read live from the Hugging Face Hub API (downloadsAllTime) This repository provides the retrieval indexes built on the passage and document corpora of the BrowseComp-Plus dataset, as used in the paper Revisiting Text Ranking in Deep Research, which has been accepted at SIGIR 2026, the 49th International ACM SIGIR Conference on Research and Development in… See the full description on the dataset page: https://huggingface.co/datasets/grill-lab/browsecomp-plus-indexes.
Indexes of Retrievers on the Passage and Document Corpora of the BrowseComp-Plus Dataset
 Total downloads since release, read live from the Hugging Face Hub API (`downloadsAllTime`)
This repository provides the retrieval indexes built on the passage and document corpora of the BrowseComp-Plus dataset, as used in the paper Revisiting Text Ranking in Deep Research, which has been accepted at SIGIR 2026, the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Code: https://github.com/ChuanMeng/text-ranking-in-deep-research
The released indexes correspond to the following retrievers:
These indexes are provided to facilitate reproducibility and enable direct evaluation of text ranking methods in the deep research setting.
Contact
If you have any questions or suggestions, please contact:
- Chuan Meng: chuan.meng@ed.ac.uk
- Litu Ou: litu.ou@ed.ac.uk
Citation
If you find this work useful, please cite:
@inproceedings{meng2026revisiting,
title={Revisiting Text Ranking in Deep Research},
author={Meng, Chuan and Ou, Litu and MacAvaney, Sean and Dalton, Jeff},
booktitle={Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {3006--3016},
url = {https://doi.org/10.1145/3805712.3808557},
doi = {10.1145/3805712.3808557},
year={2026}
}