README.md

metadata

license: mit
task_categories:
  - text-retrieval
tags:
  - retrieval-augmented-generation
  - deep-research
  - search

Passage Corpus for the BrowseComp-Plus Dataset

This repository contains the passage corpus for the BrowseComp-Plus dataset, 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 corpus consists of 2,772,255 passages. The file format follows the Tevatron data format. Each item contains three fields: docid, title, and text.

• docid denotes the unique passage identifier.
• title denotes the title of the source document from which the passage is extracted.
• text contains the passage content.

We also provide the passage corpus in Pyserini format; see here.

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},
  year={2026}
}