The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 3, saw 2
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4523, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2768, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2972, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2483, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 3, saw 2Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
GameBind counterfactual twins
Rendered two-agent scenes and their counterfactual twins, released with the anonymous submission "Counterfactual Twins Identify Perception and Binding Errors in Vision-Language Models".
Each base scene shows a target agent and a competitor agent in an 8x8 tile world. Each agent performs one action (pick up, push, hit or go to) on one object. Every action leaves a visible end state: a picked-up object is carried, a pushed object slides and leaves skid marks, a hit object cracks and leaves debris, and go to changes nothing. A twin re-renders the same scene with one controlled change, and all other pixels stay the same. Comparing a model's answers across the twins of a scene separates two causes of a wrong answer: missing the target's action and guessing, or seeing it and attributing the competitor's action to the target.
Files
| file | contents | clips | questions | images |
|---|---|---|---|---|
gamebind_twins_full.zip |
1,000 base scenes and 300 near-condition scenes with their main twins | 5,362 | 16,086 | 42,896 |
gamebind_twins_ext.zip |
further twins of the same 1,000 scenes | 2,318 | 6,954 | 18,544 |
gamebind_twins.zip |
the API subset: a separate draw of 300 base scenes and 150 near-condition scenes | 1,717 | 5,151 | 13,736 |
gamebind_twins_ext_api.zip |
further twins of the API subset | 677 | 2,031 | 5,416 |
colorshape_twins.zip |
colour-shape displays, 600 base scenes (easy display) | 4,200 | 4,200 | 3,601 |
colorshape_twins_hard.zip |
colour-shape displays, 600 base scenes (hard display) | 4,200 | 4,200 | 3,601 |
per_scene/ |
every model's answers per scene and twin, from which all results of the paper are computed |
Unzip all files in one folder. Each zip creates data/<set>/ with:
clips.json: one entry per clip, with the base scene, the twin, the events, the agents and the paths of its frames;queries.json: the questions asked on each clip, with their options and the correct answer;checks.json: the pixel checks of every twin;summary.json: the generator settings and the check summary;frames/: the images.
The frame paths in clips.json are relative to the folder where you unzip. A GameBind clip has 8 frames
(f0.png to f7.png, 512x512 pixels), and the models in the paper saw the last frame, f7.png. A colour-shape clip
is one 512x512 image.
Twins
| twin | change |
|---|---|
S |
base scene |
minus_c |
the competitor stays idle at its start tile |
minus_cue |
the target moves as in S, but its action leaves no trace |
minus_cue_minus_c |
both changes |
minus_ccue |
only the competitor's trace is deleted, the competitor still moves |
degraded_cue |
the target's trace is weakened |
swap |
the two agents exchange their events |
placebo |
an irrelevant change to the floor pixels |
S_repro |
a fresh rendering of S, used to check that rendering is exact |
In the colour-shape displays, the twins grey out the competitor shape (minus_c), the target shape (minus_cue) or
both, add a grey shape elsewhere (placebo), or exchange the two colours (swap). A blind grey image (blind) is
also included.
Questions
On every GameBind clip three questions are asked, each with four options. The joint question asks what the target agent did, and its options are the true event, two answers that mix the target's and the competitor's action and object, and the competitor's whole event. The object question and the action question ask for one part. Options are shown under rotated orders, and all twins of a base scene share the same orders. The colour-shape question asks for the colour of the target shape, with the target's colour, the competitor's colour and two absent colours as options.
Model answers
per_scene/ holds one gzip CSV per model and scene set: 19 open models on all scenes, and GPT-4.1, GPT-4o, GPT-5.5
and seven open models on the API subset. Each row is one question about one twin of one base scene, with the answer
probability of every option. The subfolders colorshape/ and photo_twins/ hold
the answers on the colour-shape displays and on the real-photo twins (numbers only). per_scene/README.md describes
the columns.
Notes
- All images are rendered. The dataset contains no photographs and no personal data.
- The renderer regenerates every frame bit for bit. Code: https://anonymous.4open.science/r/counterfactual-twins-578F
- The API subset is a separate draw from the 1,000 scenes, although the scene names repeat. A scene is identified by
its set and its
base_id.
Licence
CC BY 4.0.
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