Datasets:

EvalData
/

residualbench

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
dataset: string
forecaster: string
seed: int64
method: string
recon_mse: double
cohesion: double
vr: double
description: string
datePublished: timestamp[s]
license: string
rai:dataLimitations: string
conformsTo: string
rai:dataSocialImpact: string
prov:wasDerivedFrom: list<item: struct<@type: string, name: string, url: string, license: string>>
  child 0, item: struct<@type: string, name: string, url: string, license: string>
      child 0, @type: string
      child 1, name: string
      child 2, url: string
      child 3, license: string
url: string
rai:dataUseCases: string
recordSet: list<item: struct<@type: string, @id: string, name: string, description: string, field: list<item: s (... 173 chars omitted)
  child 0, item: struct<@type: string, @id: string, name: string, description: string, field: list<item: struct<@type (... 161 chars omitted)
      child 0, @type: string
      child 1, @id: string
      child 2, name: string
      child 3, description: string
      child 4, field: list<item: struct<@type: string, @id: string, name: string, description: string, dataType: string, s (... 83 chars omitted)
          child 0, item: struct<@type: string, @id: string, name: string, description: string, dataType: string, source: stru (... 71 chars omitted)
              child 0, @type: string
              child 1, @id: string
              child 2, name: string
              child 3, description: string
              child 4, dataType: string
              child 5, source: stru
...
ormat: string
  child 18, includes: string
  child 19, isLiveDataset: string
  child 20, jsonPath: string
  child 21, key: string
  child 22, md5: string
  child 23, parentField: string
  child 24, path: string
  child 25, recordSet: string
  child 26, references: string
  child 27, regex: string
  child 28, repeated: string
  child 29, samplingRate: string
  child 30, replace: string
  child 31, sc: string
  child 32, separator: string
  child 33, source: string
  child 34, subField: string
  child 35, transform: string
rai:dataAnnotationProtocol: string
distribution: list<item: struct<@type: string, @id: string, name: string, description: string, contentUrl: string, (... 90 chars omitted)
  child 0, item: struct<@type: string, @id: string, name: string, description: string, contentUrl: string, encodingFo (... 78 chars omitted)
      child 0, @type: string
      child 1, @id: string
      child 2, name: string
      child 3, description: string
      child 4, contentUrl: string
      child 5, encodingFormat: string
      child 6, md5: string
      child 7, containedIn: struct<@id: string>
          child 0, @id: string
      child 8, includes: string
@type: string
rai:dataPreprocessingProtocol: string
prov:wasGeneratedBy: struct<@type: string, rdfs:label: string, description: string>
  child 0, @type: string
  child 1, rdfs:label: string
  child 2, description: string
rai:socialImpact: string
version: string
rai:personalSensitiveInformation: string
rai:dataCollection: string
to
{'@context': {'@language': Value('string'), '@vocab': Value('string'), 'citeAs': Value('string'), 'column': Value('string'), 'conformsTo': Value('string'), 'cr': Value('string'), 'rai': Value('string'), 'data': {'@id': Value('string'), '@type': Value('string')}, 'dataType': {'@id': Value('string'), '@type': Value('string')}, 'dct': Value('string'), 'equivalentProperty': Value('string'), 'examples': {'@id': Value('string'), '@type': Value('string')}, 'extract': Value('string'), 'field': Value('string'), 'fileProperty': Value('string'), 'fileObject': Value('string'), 'fileSet': Value('string'), 'format': Value('string'), 'includes': Value('string'), 'isLiveDataset': Value('string'), 'jsonPath': Value('string'), 'key': Value('string'), 'md5': Value('string'), 'parentField': Value('string'), 'path': Value('string'), 'recordSet': Value('string'), 'references': Value('string'), 'regex': Value('string'), 'repeated': Value('string'), 'samplingRate': Value('string'), 'replace': Value('string'), 'sc': Value('string'), 'separator': Value('string'), 'source': Value('string'), 'subField': Value('string'), 'transform': Value('string')}, '@type': Value('string'), 'conformsTo': Value('string'), 'name': Value('string'), 'description': Value('string'), 'url': Value('string'), 'version': Value('string'), 'license': Value('string'), 'citeAs': Value('string'), 'datePublished': Value('timestamp[s]'), 'creator': List({'@type': Value('string'), 'name': Value('string')}), 'rai:dataCollection': Value('string'), 'rai:dataPreprocessingProtocol': Value('string'), 'rai:dataAnnotationProtocol': Value('string'), 'rai:dataUseCases': Value('string'), 'rai:dataLimitations': Value('string'), 'rai:dataBiases': Value('string'), 'rai:personalSensitiveInformation': Value('string'), 'rai:socialImpact': Value('string'), 'rai:dataSocialImpact': Value('string'), 'rai:isSyntheticData': Value('bool'), 'rai:hasSyntheticData': Value('string'), 'prov:wasDerivedFrom': List({'@type': Value('string'), 'name': Value('string'), 'url': Value('string'), 'license': Value('string')}), 'prov:wasGeneratedBy': {'@type': Value('string'), 'rdfs:label': Value('string'), 'description': Value('string')}, 'distribution': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'contentUrl': Value('string'), 'encodingFormat': Value('string'), 'md5': Value('string'), 'containedIn': {'@id': Value('string')}, 'includes': Value('string')}), 'recordSet': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'field': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'dataType': Value('string'), 'source': {'fileObject': {'@id': Value('string')}, 'extract': {'jsonPath': Value('string')}}})})}
because column names don't match
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 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, 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 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, 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/json/json.py", line 295, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              dataset: string
              forecaster: string
              seed: int64
              method: string
              recon_mse: double
              cohesion: double
              vr: double
              description: string
              datePublished: timestamp[s]
              license: string
              rai:dataLimitations: string
              conformsTo: string
              rai:dataSocialImpact: string
              prov:wasDerivedFrom: list<item: struct<@type: string, name: string, url: string, license: string>>
                child 0, item: struct<@type: string, name: string, url: string, license: string>
                    child 0, @type: string
                    child 1, name: string
                    child 2, url: string
                    child 3, license: string
              url: string
              rai:dataUseCases: string
              recordSet: list<item: struct<@type: string, @id: string, name: string, description: string, field: list<item: s (... 173 chars omitted)
                child 0, item: struct<@type: string, @id: string, name: string, description: string, field: list<item: struct<@type (... 161 chars omitted)
                    child 0, @type: string
                    child 1, @id: string
                    child 2, name: string
                    child 3, description: string
                    child 4, field: list<item: struct<@type: string, @id: string, name: string, description: string, dataType: string, s (... 83 chars omitted)
                        child 0, item: struct<@type: string, @id: string, name: string, description: string, dataType: string, source: stru (... 71 chars omitted)
                            child 0, @type: string
                            child 1, @id: string
                            child 2, name: string
                            child 3, description: string
                            child 4, dataType: string
                            child 5, source: stru
              ...
              ormat: string
                child 18, includes: string
                child 19, isLiveDataset: string
                child 20, jsonPath: string
                child 21, key: string
                child 22, md5: string
                child 23, parentField: string
                child 24, path: string
                child 25, recordSet: string
                child 26, references: string
                child 27, regex: string
                child 28, repeated: string
                child 29, samplingRate: string
                child 30, replace: string
                child 31, sc: string
                child 32, separator: string
                child 33, source: string
                child 34, subField: string
                child 35, transform: string
              rai:dataAnnotationProtocol: string
              distribution: list<item: struct<@type: string, @id: string, name: string, description: string, contentUrl: string, (... 90 chars omitted)
                child 0, item: struct<@type: string, @id: string, name: string, description: string, contentUrl: string, encodingFo (... 78 chars omitted)
                    child 0, @type: string
                    child 1, @id: string
                    child 2, name: string
                    child 3, description: string
                    child 4, contentUrl: string
                    child 5, encodingFormat: string
                    child 6, md5: string
                    child 7, containedIn: struct<@id: string>
                        child 0, @id: string
                    child 8, includes: string
              @type: string
              rai:dataPreprocessingProtocol: string
              prov:wasGeneratedBy: struct<@type: string, rdfs:label: string, description: string>
                child 0, @type: string
                child 1, rdfs:label: string
                child 2, description: string
              rai:socialImpact: string
              version: string
              rai:personalSensitiveInformation: string
              rai:dataCollection: string
              to
              {'@context': {'@language': Value('string'), '@vocab': Value('string'), 'citeAs': Value('string'), 'column': Value('string'), 'conformsTo': Value('string'), 'cr': Value('string'), 'rai': Value('string'), 'data': {'@id': Value('string'), '@type': Value('string')}, 'dataType': {'@id': Value('string'), '@type': Value('string')}, 'dct': Value('string'), 'equivalentProperty': Value('string'), 'examples': {'@id': Value('string'), '@type': Value('string')}, 'extract': Value('string'), 'field': Value('string'), 'fileProperty': Value('string'), 'fileObject': Value('string'), 'fileSet': Value('string'), 'format': Value('string'), 'includes': Value('string'), 'isLiveDataset': Value('string'), 'jsonPath': Value('string'), 'key': Value('string'), 'md5': Value('string'), 'parentField': Value('string'), 'path': Value('string'), 'recordSet': Value('string'), 'references': Value('string'), 'regex': Value('string'), 'repeated': Value('string'), 'samplingRate': Value('string'), 'replace': Value('string'), 'sc': Value('string'), 'separator': Value('string'), 'source': Value('string'), 'subField': Value('string'), 'transform': Value('string')}, '@type': Value('string'), 'conformsTo': Value('string'), 'name': Value('string'), 'description': Value('string'), 'url': Value('string'), 'version': Value('string'), 'license': Value('string'), 'citeAs': Value('string'), 'datePublished': Value('timestamp[s]'), 'creator': List({'@type': Value('string'), 'name': Value('string')}), 'rai:dataCollection': Value('string'), 'rai:dataPreprocessingProtocol': Value('string'), 'rai:dataAnnotationProtocol': Value('string'), 'rai:dataUseCases': Value('string'), 'rai:dataLimitations': Value('string'), 'rai:dataBiases': Value('string'), 'rai:personalSensitiveInformation': Value('string'), 'rai:socialImpact': Value('string'), 'rai:dataSocialImpact': Value('string'), 'rai:isSyntheticData': Value('bool'), 'rai:hasSyntheticData': Value('string'), 'prov:wasDerivedFrom': List({'@type': Value('string'), 'name': Value('string'), 'url': Value('string'), 'license': Value('string')}), 'prov:wasGeneratedBy': {'@type': Value('string'), 'rdfs:label': Value('string'), 'description': Value('string')}, 'distribution': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'contentUrl': Value('string'), 'encodingFormat': Value('string'), 'md5': Value('string'), 'containedIn': {'@id': Value('string')}, 'includes': Value('string')}), 'recordSet': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'field': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'dataType': Value('string'), 'source': {'fileObject': {'@id': Value('string')}, 'extract': {'jsonPath': Value('string')}}})})}
              because column names don't match

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ResidualBench

A benchmark and evaluation protocol for cross-model forecast failure mode discovery, accompanying the NeurIPS 2026 Evaluations & Datasets Track submission "ResidualBench: A Benchmark and Evaluation Protocol for Cross-Model Forecast Failure Mode Discovery".

This repository hosts the small artifacts required for review and reproduction:

croissant.json — Croissant 1.0 dataset metadata with the full RAI extension.
residualbench-0.1.0.tar.gz — pip-installable Python package implementing the fit / encode / reconstruct method protocol, motif-level metrics, Hungarian alignment, and the lag-1 / learned selectors.
results/*.json — pre-computed aggregated benchmark results across all 855 (dataset, forecaster, method, seed) cells.
LICENSE, REPRODUCE.md — license and step-by-step reproduction guide.

The full per-window residual tensors (residuals.pt, ~123 GB) are not stored in this repository because of size. They can be regenerated from public source datasets in a few GPU-hours by following REPRODUCE.md Step 2 ("Train forecasters and collect residuals"). Optionally, a tar archive of the residuals can be uploaded as an additional release file via the upload_residuals_to_hf.py helper that ships with the source repository.

Provenance

ResidualBench builds on nine public time-series datasets (cited in croissant.json under prov:wasDerivedFrom):

Dataset	Source	License
ETTh1, ETTh2, ETTm1, ETTm2	https://github.com/zhouhaoyi/ETDataset	CC-BY-4.0
Weather	https://www.bgc-jena.mpg.de/wetter/	CC-BY-4.0
Electricity	UCI ML Repository (321)	CC-BY-4.0
Traffic (PEMS)	https://pems.dot.ca.gov/	Public domain
Exchange	https://github.com/laiguokun/multivariate-time-series-data	CC-BY-4.0
ILI	CDC FluView	Public domain

ResidualBench itself does not introduce a new raw dataset.

Headline numbers (re-derivable from `results/all_results.json`)

855 of 945 configurations (Spectral omitted on 6 high-dim datasets).
Cross-forecaster Hungarian alignment 0.23–0.57, $4{-}11\times$ above shuffled null on most datasets.
Lag-1 model selector beats best fixed forecaster by up to 17 % on temporal hold-out.
Cohesion (TopK, mean of 5 forecasters $\times$ 3 seeds): ETTh1 0.481, ETTh2 0.712, ETTm1 0.656, ETTm2 0.615, Weather 0.652, Electricity 0.558, Traffic 0.304, Exchange 0.899, ILI 0.962.

Reproducing

pip install residualbench-0.1.0.tar.gz
python -c "from residualbench import ResidualBench; print(ResidualBench.__doc__)"

For end-to-end regeneration of the residual tensors and benchmark numbers, see REPRODUCE.md.

Citation

@inproceedings{residualbench2026,
  title={ResidualBench: A Benchmark and Evaluation Protocol for Cross-Model Forecast Failure Mode Discovery},
  author={Anonymous},
  booktitle={NeurIPS 2026 Evaluations and Datasets Track},
  year={2026}
}

License

MIT for the harness and metadata. Each upstream dataset retains its original license; see croissant.json for details.

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