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mikezhu
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chord-experiments-data

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Text Generation

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English

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100K<n<1M

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Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
included: list<item: string>
  child 0, item: string
skipped: list<item: null>
  child 0, item: null
position: string
seed: int64
conditions: list<item: struct<name: string, family: string, group: string, experiment: string, kind: string, rol (... 63 chars omitted)
  child 0, item: struct<name: string, family: string, group: string, experiment: string, kind: string, role: string,  (... 51 chars omitted)
      child 0, name: string
      child 1, family: string
      child 2, group: string
      child 3, experiment: string
      child 4, kind: string
      child 5, role: string
      child 6, dose: double
      child 7, dose_kind: string
      child 8, criterion: string
corpus: string
to
{'corpus': Value('string'), 'position': Value('string'), 'seed': Value('int64'), 'conditions': List({'name': Value('string'), 'family': Value('string'), 'group': Value('string'), 'experiment': Value('string'), 'kind': Value('string'), 'role': Value('string'), 'dose': Value('float64'), 'dose_kind': Value('string'), 'criterion': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              included: list<item: string>
                child 0, item: string
              skipped: list<item: null>
                child 0, item: null
              position: string
              seed: int64
              conditions: list<item: struct<name: string, family: string, group: string, experiment: string, kind: string, rol (... 63 chars omitted)
                child 0, item: struct<name: string, family: string, group: string, experiment: string, kind: string, role: string,  (... 51 chars omitted)
                    child 0, name: string
                    child 1, family: string
                    child 2, group: string
                    child 3, experiment: string
                    child 4, kind: string
                    child 5, role: string
                    child 6, dose: double
                    child 7, dose_kind: string
                    child 8, criterion: string
              corpus: string
              to
              {'corpus': Value('string'), 'position': Value('string'), 'seed': Value('int64'), 'conditions': List({'name': Value('string'), 'family': Value('string'), 'group': Value('string'), 'experiment': Value('string'), 'kind': Value('string'), 'role': Value('string'), 'dose': Value('float64'), 'dose_kind': Value('string'), 'criterion': Value('string')})}
              because column names don't match

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CHORD experiment corpora

Text corpora and cached encoder features behind every table and figure of the paper Coherence-Aware Distributional Evaluation of Open-Ended Text Generation: the counterfactual evaluation set, the unconditional-generation samples and human reference pools, and the prefix-continuation, human-agreement, QA-faithfulness and appendix texts. The tree mirrors the experiments repository (CHORD-Experiment), so after

python scripts/download_data.py --repo mikezhu/chord-experiments-data            # texts
python scripts/download_data.py --repo mikezhu/chord-experiments-data --features # + cached features

every config resolves. MANIFEST-experiments.tsv lists every file with its size and sha256. The students' training data is in a separate dataset (chord-distill-data).

Code: https://github.com/MAPS-research/CHORD

Path	What
`outputs/counterfactual/meta_eval/`	counterfactual evaluation set (Table 1): texts per condition and the conditions manifest
`outputs/casestudy/unconditional_generation/`	Table 2: 10 seeds x 500 samples per generator, human reference / held-out pools
`outputs/casestudy/single_fold/`	single-fold unconditional corpora (quick student check)
`outputs/casestudy/prefix_continuation/`	prefixes, human continuations and generator continuations (Fig. 5)
`outputs/casestudy/human_agreement/`	GPT-2 texts with public human pairwise judgments and their Bradley-Terry scores (Table 3)
`outputs/casestudy/qa_faithfulness/`	source-conditioned QA-faithfulness texts (appendix)
`outputs/experiments/position_robustness/`	failure-position corpus (appendix)
`outputs/casestudy/unconditional_generation/features/`, `cache/` (features part)	Qwen3.5-27B features of the Table-2 folds; GPT-2-large gen-PPL cache
`outputs/experiments/position_robustness/feats/` (features part)	Qwen3.5-9B features of the failure-position corpus

Feature files are float32 .npy matrices, one row per line of the text file they are named after.

License

Each text keeps the license of its source, and an edited or spliced passage follows the license of the passage it was made from. Generated text is listed with the terms of the model that produced it; none of these models restricts how its outputs may be used. Everything else in this dataset (its organization, the manifests and labels, bt_scores.csv, and the cached features) is released under CC BY 4.0.

Source	Role	License or terms
OpenWebText (`Skylion007/openwebtext`)	human reference and held-out pools, counterfactual parents, prefixes and human continuations	CC0 1.0
Wikipedia via WikiText-103 (`Salesforce/wikitext`)	counterfactual parents	CC BY-SA 3.0 and GFDL
Reddit TL;DR (`trl-lib/tldr`)	counterfactual parents	none stated on `trl-lib/tldr`; it is OpenAI's filtered subset of Webis-TLDR-17, released under CC BY 4.0
SQuAD v1.1 (`rajpurkar/squad`)	QA-faithfulness texts	CC BY-SA 4.0
MAUVE human evaluation (Pillutla et al., 2021; `krishnap25/mauve-experiments`)	human-agreement texts and the judgments behind `bt_scores.csv`	none stated in the source repository
GPT-2 WebText test split (`openai/gpt-2-output-dataset`)	human-agreement reference	MIT
GPT-2 small, medium, large, XL	generations (Table 2, Figure 5, human agreement)	MIT
MDLM (`kuleshov-group/mdlm-owt`), LangFlow (`Continuous-Rivals-Discrete/langflow-owt`)	generations	Apache-2.0
SEDD (`louaaron/sedd-small`)	generations	code MIT; the checkpoint states no license
ELF (`embedded-language-flows`)	generations	the checkpoints state no license
Qwen3-30B-A3B, Mistral-Small-24B-Instruct-2501	edited variants	Apache-2.0
Qwen3.5-27B, Qwen3.5-9B; GPT-2-large	cached features; gen-PPL cache	Apache-2.0; MIT

Citation

@misc{liu2026coherenceawaredistributionalevaluationopenended,
      title={Coherence-Aware Distributional Evaluation of Open-Ended Text Generation},
      author={Jinnuo Liu and Junhao Zhu and Weifeng Jiang and Haoming Liu and Hongyi Wen},
      year={2026},
      eprint={2609.34240},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2609.34240},
}

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Paper for mikezhu/chord-experiments-data

Coherence-Aware Distributional Evaluation of Open-Ended Text Generation

Paper • 2609.34240 • Published 3 days ago

CHORD experiment corpora

Contents

License

Citation

Paper for mikezhu/chord-experiments-data