Datasets:

latentMO
/

cotcontrol-gpqafull-20261027

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train

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:    CastError
Message:      Couldn't cast
dataset: string
item_idx: int64
answer: string
samples: int64
cot_correct: int64
nocot_correct: int64
nocot_unparsed: int64
cot_tokens_median: double
cot_truncated: int64
1 - base accuracy without a CoT (24 samples) | manytypes2e s170: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
  child 0, slope_raw: double
  child 1, slope_raw_ci: list<item: double>
      child 0, item: double
  child 2, slope_len_controlled: double
  child 3, slope_len_controlled_ci: list<item: double>
      child 0, item: double
  child 4, median_tokens: double
  child 5, n_rows: int64
1 - base accuracy without a CoT (24 samples) | manytypes2c s140: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
  child 0, slope_raw: double
  child 1, slope_raw_ci: list<item: double>
      child 0, item: double
  child 2, slope_len_controlled: double
  child 3, slope_len_controlled_ci: list<item: double>
      child 0, item: double
  child 4, median_tokens: double
  child 5, n_rows: int64
1 - base accuracy with a CoT (24 samples) | manytypes2c s140: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
  child 0, slope_raw: double
  child 1, slope_raw_ci: list<item: double>
      child 0, item: double
  child 2, slope_len_controlled: double
  child 3, slope_len_controlled_ci: list<item: double>
     
...
ed_ci: list<item: double>
      child 0, item: double
  child 4, median_tokens: double
  child 5, n_rows: int64
1 - base accuracy without a CoT (24 samples) | base: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
  child 0, slope_raw: double
  child 1, slope_raw_ci: list<item: double>
      child 0, item: double
  child 2, slope_len_controlled: double
  child 3, slope_len_controlled_ci: list<item: double>
      child 0, item: double
  child 4, median_tokens: double
  child 5, n_rows: int64
1 - base accuracy with a CoT (24 samples) | manytypes2e s170: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
  child 0, slope_raw: double
  child 1, slope_raw_ci: list<item: double>
      child 0, item: double
  child 2, slope_len_controlled: double
  child 3, slope_len_controlled_ci: list<item: double>
      child 0, item: double
  child 4, median_tokens: double
  child 5, n_rows: int64
1 - base accuracy with a CoT (24 samples) | grpo3 s100: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
  child 0, slope_raw: double
  child 1, slope_raw_ci: list<item: double>
      child 0, item: double
  child 2, slope_len_controlled: double
  child 3, slope_len_controlled_ci: list<item: double>
      child 0, item: double
  child 4, median_tokens: double
  child 5, n_rows: int64
to
{'1 - base accuracy with a CoT (24 samples) | base': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | grpo3 s100': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | manytypes1b s150': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | manytypes2c s140': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | manytypes2e s170': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | base': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | grpo3 s100': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | manytypes1b s150': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | manytypes2c s140': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | manytypes2e s170': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              dataset: string
              item_idx: int64
              answer: string
              samples: int64
              cot_correct: int64
              nocot_correct: int64
              nocot_unparsed: int64
              cot_tokens_median: double
              cot_truncated: int64
              1 - base accuracy without a CoT (24 samples) | manytypes2e s170: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
                child 0, slope_raw: double
                child 1, slope_raw_ci: list<item: double>
                    child 0, item: double
                child 2, slope_len_controlled: double
                child 3, slope_len_controlled_ci: list<item: double>
                    child 0, item: double
                child 4, median_tokens: double
                child 5, n_rows: int64
              1 - base accuracy without a CoT (24 samples) | manytypes2c s140: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
                child 0, slope_raw: double
                child 1, slope_raw_ci: list<item: double>
                    child 0, item: double
                child 2, slope_len_controlled: double
                child 3, slope_len_controlled_ci: list<item: double>
                    child 0, item: double
                child 4, median_tokens: double
                child 5, n_rows: int64
              1 - base accuracy with a CoT (24 samples) | manytypes2c s140: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
                child 0, slope_raw: double
                child 1, slope_raw_ci: list<item: double>
                    child 0, item: double
                child 2, slope_len_controlled: double
                child 3, slope_len_controlled_ci: list<item: double>
                   
              ...
              ed_ci: list<item: double>
                    child 0, item: double
                child 4, median_tokens: double
                child 5, n_rows: int64
              1 - base accuracy without a CoT (24 samples) | base: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
                child 0, slope_raw: double
                child 1, slope_raw_ci: list<item: double>
                    child 0, item: double
                child 2, slope_len_controlled: double
                child 3, slope_len_controlled_ci: list<item: double>
                    child 0, item: double
                child 4, median_tokens: double
                child 5, n_rows: int64
              1 - base accuracy with a CoT (24 samples) | manytypes2e s170: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
                child 0, slope_raw: double
                child 1, slope_raw_ci: list<item: double>
                    child 0, item: double
                child 2, slope_len_controlled: double
                child 3, slope_len_controlled_ci: list<item: double>
                    child 0, item: double
                child 4, median_tokens: double
                child 5, n_rows: int64
              1 - base accuracy with a CoT (24 samples) | grpo3 s100: struct<slope_raw: double, slope_raw_ci: list<item: double>, slope_len_controlled: double, slope_len_ (... 72 chars omitted)
                child 0, slope_raw: double
                child 1, slope_raw_ci: list<item: double>
                    child 0, item: double
                child 2, slope_len_controlled: double
                child 3, slope_len_controlled_ci: list<item: double>
                    child 0, item: double
                child 4, median_tokens: double
                child 5, n_rows: int64
              to
              {'1 - base accuracy with a CoT (24 samples) | base': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | grpo3 s100': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | manytypes1b s150': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | manytypes2c s140': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy with a CoT (24 samples) | manytypes2e s170': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | base': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | grpo3 s100': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | manytypes1b s150': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | manytypes2c s140': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}, '1 - base accuracy without a CoT (24 samples) | manytypes2e s170': {'slope_raw': Value('float64'), 'slope_raw_ci': List(Value('float64')), 'slope_len_controlled': Value('float64'), 'slope_len_controlled_ci': List(Value('float64')), 'median_tokens': Value('float64'), 'n_rows': Value('int64')}}
              because column names don't match

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CoT-control compliance vs no-CoT accuracy on GPQA (gpt-oss-120b and CoT-control organisms), 2026-10-27

Raw data behind the full-GPQA analyses in johntrob14/tricky_little_guys, cot-control/results/difficulty/NOTES.md and cot-control/results/trainset_acc/NOTES.md.

Models: base openai/gpt-oss-120b and three CoT-control GRPO organisms on Tinker: grpo3 step 100, manytypes1b step 150, manytypes2e step 170 (checkpoint paths in each run's config.json).

transfer/gpqafull-<model>[-seed1]/: the CoT-control transfer eval (cot-control/rl/transfer_eval.py --item-set gpqafull) on 360 GPQA items (the 427 with keywords minus the 67 GPQA questions manytypes2e trained on), the 21 manytypes2 control types, F0 wording, requirement in the user turn, one sample per item and type per seed (seeds 0 and 1), plus a no-requirement baseline arm. gens.jsonl = prompts, full generations, programmatic grades; judgments.jsonl = requirement, ignore_question and mention judgments (base gpt-oss-120b on Tinker); summary.md per type.
difficulty/gpqafull_<model>.jsonl: per item, 24 no-CoT samples (empty analysis channel, ANSWER: prefilled) and 8 CoT samples (cot-control/rl/item_difficulty.py); gpqafull_base_nocot48.jsonl: base, 48 no-CoT samples. gpqa_base.jsonl: base on the 36-item transfer set. gpqa_scatter.json, compliance_vs_difficulty_gpqa.json: fitted slopes.
trainset_acc/: organism vs base accuracy with and without a CoT on training questions drawn vs never drawn (cot-control/rl/trainset_acc.py).

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