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SISAP2026

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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ArrowInvalid
Message:      Column 1 named itest expected length 200000 but got length 10000
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                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 2083, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 544, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 383, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 87, in _generate_tables
                  pa_table = _recursive_load_arrays(h5, self.info.features, start, end)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 283, in _recursive_load_arrays
                  return pa.Table.from_pydict(batch_dict)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 1985, in pyarrow.lib._Tabular.from_pydict
                File "pyarrow/table.pxi", line 6401, in pyarrow.lib._from_pydict
                File "pyarrow/table.pxi", line 4912, in pyarrow.lib.Table.from_arrays
                File "pyarrow/table.pxi", line 4256, in pyarrow.lib.Table.validate
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Column 1 named itest expected length 200000 but got length 10000

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This repository contains the development data files used in the SISAP2026 indexing challenge.

Datasets for previous editions:

Datasets

  • WIKIPEDIA (English articles):

    • repo: https://huggingface.co/datasets/wikimedia/wikipedia
    • BGE m3 model: https://huggingface.co/BAAI/bge-m3
    • File: benchmark-dev-wikipedia-bge-m3.h5
    • similarity: Cosine / dot product
    • Content of the h5 file:
      • dataset train: a 6.35 million vector database, i.e., a matrix of size $1024 \times 6350000$ (f16)
      • group itrain: collection of data related to in-distribution queries (articles removed from the English Wikipedia corpus):
        • itest/queries: a 10'000 vector database, i.e., a matrix of size $1024 \times 10000$ (f16)
        • itest/knns: the gold-standard identifiers for the 1000 nearest neighbors of itest/queries in train, i.e., a matrix $1000 \times 10000$ (i32).
        • itest/dists: the gold-standard distances (1-dot) for the 1000 nearest neighbors of itest/queries in train, i.e., a matrix $1000 \times 10000$ (f32).
      • group otrain: collection of data related to out-of-distribution queries (same model in random articles from the Spanish Wikipedia, i.e., cross-lingual retrieval):
        • otest/queries: a 10'000 vector database, i.e., a matrix of size $1024 \times 10000$ (f16)
        • otest/knns: the gold-standard identifiers for the 1000 nearest neighbors of itest/queries in train, i.e., a matrix $1000 \times 10000$ (i32).
        • otest/dists: the gold-standard distances (1-dot) for the 1000 nearest neighbors of itest/queries in train, i.e., a matrix $1000 \times 10000$ (f32).
      • group allknn:
        • allknn/knns: the gold-standard identifiers for the all-knn graph of train i.e., a matrix $32 \times 6350000$ (i32).
        • allknn/dists: the gold-standard distances (1-dot) for the all-knn graph of train i.e., a matrix $32 \times 6350000$ (f32).

  • WIKIPEDIA Small (English articles):

    • This is small version of WIKIPEDIA database for testing and developing purposes, more precisely, the train dataset is a 200k vector database.
    • File: benchmark-dev-wikipedia-bge-m3-small.h5

Note: h5py/HDF5.jl packages read matrices in the expected platform order, so be careful since it could permute dimensions w.r.t what is here explained, however, the final order is what is expected anyway for fast implementations. ```

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