Dataset Viewer
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: JSON parse error: Missing a comma or ']' after an array element. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
~~~~~~~~~^
ujson_loads(json, precise_float=self.precise_float), dtype=None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/core/frame.py", line 782, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 680, in _extract_index
raise ValueError(
"Mixing dicts with non-Series may lead to ambiguous ordering."
)
ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.
During handling of the above exception, another exception occurred:
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 478, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Missing a comma or ']' after an array element. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Gemma-2-9B AO-blindness crossover — raw verbalizer outputs
Raw, per-cell Activation Oracle (AO) verbalizations from the faithful AO-blindness
crossover experiment on gemma-2-9b-it. Every AO is run against every taboo model-organism
(MO); this dataset holds the full generated responses behind the distilled scores and
figures that live in the code repo (activation_oracles/experiments/crossover/).
The experiment tests whether an off-recipe AO (trained on top of a quirked MO instead of the clean base) goes blind to its own host's quirk while still seeing foreign quirks.
Contents
| dir | elicitation | grid |
|---|---|---|
direct/ |
extraction / jailbreak prompts ("output the secret word") | 21 taboo words × 21 MOs + on-recipe base oracle |
standard/ |
benign hint-seeking ("Hint me." / "Clue me in.") | same 21×21 grid |
think_suppress/ |
think / suppress / neutral priming on an unrelated number-generation task | 4 taboo MOs × faithful oracle + base, 2 probe sites |
direct/ also contains green_add/ — the incrementally-added green oracle column.
File format
Each crossover_<oracle>.json (one per AO):
config,verbalizer_lora_path,host_lora_pathresults: one record per (target MO × verbalizer prompt × context prompt):target_lora_path,context_prompt,verbalizer_prompt,ground_truth,act_keyfull_sequence_responses/segment_responses/token_responses— the AO's generated textcontext_input_ids,num_tokens
scores_lora.json in each dir is the distilled per-(oracle, MO) recovery summary
(pooled / best-prompt accuracy), and the think_suppress/ one also carries Δthink / Δsupp.
Reproduce
- crossover grids:
experiments/crossover/pipeline/crossover_eval.py→score_crossover.py - think/suppress:
experiments/crossover/think_suppress/think_suppress_eval.py→think_suppress_score.py
These raw outputs (~450 MB) are fully regenerable and are stored here to keep them out of git;
the code repo keeps only the small scores_lora.json + figures.
- Downloads last month
- 40