The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 2 was different:
embedding_offset: int64
num_embeddings: int64
num_passages: int64
vs
text: int64
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3608, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2368, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2573, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2082, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 588, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Schema at index 2 was different:
embedding_offset: int64
num_embeddings: int64
num_passages: int64
vs
text: int64Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Indexes of Retrievers on the Passage and Document Corpora of the BrowseComp-Plus Dataset
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:
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}
}
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