Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Column(/episodes/[]/rigid_objs/[]/[]) changed from string to number in row 0
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
df = pandas_read_json(f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
obj = self._get_object_parser(self.data)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
self._parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1402, in _parse
self.obj = DataFrame(
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/frame.py", line 778, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
File "/src/services/worker/.venv/lib/python3.9/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 "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 680, in _extract_index
raise ValueError(
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/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
for key, pa_table in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 177, in _generate_tables
raise e
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/episodes/[]/rigid_objs/[]/[]) changed from string to number 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.
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Check out the documentation for more information.
2026 ICLR Submission
Current vision-language models (VLMs) struggle with long-term memory in embodied tasks. To address this, we introduce FindingDory, a benchmark in Habitat that evaluates memory-based reasoning across 60 long-horizon tasks.
In this repo, we release the FindingDory Habitat Dataset. The episode dataset is used to run online evaluations with the Habitat simulator using VLM-based navigation agents. Each episode involves a robot performing multiple pick-place object interactions. The agent then needs to execute actions in the simulator complete the tasks specified in the FindingDory benchmark.
We also release datasets that can be used for supervised finetuning of multimodal LLMs using the video-task pairs in FindingDory
Habitat Dataset Structure
This repository contains data and models for the findingdory-habitat package, structured into two main components: findingdory and imgnav.
findingdory
| File/Folder | Description |
|---|---|
| train/ | Training split of the habitat dataset. |
├── episodes.json.gz |
Encoded JSON file containing episode metadata for training episodes. |
├── transformations.npy |
NumPy array of transformation matrices (of each rigid object in simulator). |
└── viewpoints.npy |
NumPy array of viewpoints (camera poses of all objects/receptacles). |
| val/ | Validation split of the habitat dataset. |
├── episodes.json.gz |
Encoded JSON file containing episode metadata for validation episodes. |
├── transformations.npy |
NumPy array of transformation matrices (of each rigid object in simulator). |
└── viewpoints.npy |
NumPy array of viewpoints (camera poses of all objects/receptacles). |
findingdory_imagenav
| File/Folder | Description |
|---|---|
| dataset/ | Image navigation dataset (split into train and val). |
├── train/ |
Training data for the image navigation task. |
└── val/ |
Validation data for the image navigation task. |
| policy_ckpt/ | Policy checkpoint files (trained navigation policies). |
└── ckpt.17.pth |
PyTorch checkpoint file containing trained policy weights. |
| pretrained_vis_enc/ | Pretrained visual encoder weights. |
└── ckpt.16.pth |
PyTorch checkpoint file for the pretrained visual encoder used in imagenav training. |
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