Datasets:
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: CastError
Message: Couldn't cast
image_idx: int64
rng_seed: double
params: struct<c: double>
child 0, c: double
output_sha256: string
master_seed: int64
n_images: int64
function_module: string
image_shape: list<item: int64>
child 0, item: int64
output_npy_sha256: string
function_name: string
severity: int64
wall_time_sec: double
corruption: string
dataset: string
split: string
to
{'dataset': Value('string'), 'corruption': Value('string'), 'severity': Value('int64'), 'split': Value('string'), 'master_seed': Value('int64'), 'n_images': Value('int64'), 'image_shape': List(Value('int64')), 'function_module': Value('string'), 'function_name': Value('string'), 'wall_time_sec': Value('float64'), 'output_npy_sha256': 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 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 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
image_idx: int64
rng_seed: double
params: struct<c: double>
child 0, c: double
output_sha256: string
master_seed: int64
n_images: int64
function_module: string
image_shape: list<item: int64>
child 0, item: int64
output_npy_sha256: string
function_name: string
severity: int64
wall_time_sec: double
corruption: string
dataset: string
split: string
to
{'dataset': Value('string'), 'corruption': Value('string'), 'severity': Value('int64'), 'split': Value('string'), 'master_seed': Value('int64'), 'n_images': Value('int64'), 'image_shape': List(Value('int64')), 'function_module': Value('string'), 'function_name': Value('string'), 'wall_time_sec': Value('float64'), 'output_npy_sha256': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
CILN-Bench: MNIST
Instance-dependent label noise benchmarks built from controlled input corruptions.
This dataset is the MNIST component of CILN-Bench. We corrupt the MNIST noisy-label-train (NLT) split with 14 standard image corruptions (MNIST-C plus structural operators), then let a fixed voter pool (4 architectures) classify the corrupted images. The resulting soft labels are released as a noisy-label benchmark.
After a low-impact filter, 30 settings are released (out of 37 candidates).
- Code, examples, and reproducibility tests: https://github.com/sh-islam/ciln-bench
- Companion datasets: ciln-bench-cifar10, ciln-bench-adult
Settings released
| Family | Corruptions |
|---|---|
| Noise | shot_noise, impulse_noise, spatter |
| Blur | glass_blur, motion_blur |
| Geometric | rotate, shear, translate, scale |
| Weather/Digital | fog, brightness |
| Structural | canny_edges, dotted_line, stripe, zigzag |
The Structural corruptions are binary operators and therefore contribute one setting each rather than three severity levels.
Noise rate ranges from 5.9% to 71.5% across the 30 released settings.
Voter pool
4 voters: LeNet-5, MLP, ResNet-20, DeiT3-Small.
Repository layout
settings/
├── brightness_sev1/
│ ├── noisy_label_train/
│ │ ├── images.npy # (27000, 28, 28, 1) uint8 — corrupted images
│ │ ├── labels.npy # (27000,) int64
│ │ ├── softmax_lenet5.npy # (27000, 10) float32
│ │ ├── softmax_mlp.npy
│ │ ├── softmax_resnet20.npy
│ │ ├── softmax_deit3_small.npy
│ │ ├── avg_softmax.npy
│ │ ├── manifest.json
│ │ └── params.jsonl
│ └── noisy_label_valid/
│ └── ... (same structure)
└── ... (30 settings total)
How to load
import numpy as np
from huggingface_hub import snapshot_download
local = snapshot_download(
repo_id="sh-islam/ciln-bench-mnist",
repo_type="dataset",
allow_patterns=["settings/rotate_sev5/noisy_label_train/*"],
)
images = np.load(f"{local}/settings/rotate_sev5/noisy_label_train/images.npy")
labels = np.load(f"{local}/settings/rotate_sev5/noisy_label_train/labels.npy")
print(images.shape, labels.shape)
# (27000, 28, 28, 1) (27000,)
allow_patterns is a filter that limits which files get downloaded. Pass a glob (or a list of globs) and only matching files come down. Omit it to download the full dataset.
Citation
@inproceedings{cilnbench2027,
title = {CILN-Bench: A Benchmark for Corruption-Induced Label Noise},
author = {Islam, Shadman and Kristiadi, Agustinus and Milani, Mostafa},
booktitle = {ICDE},
year = {2027}
}
License
MIT.
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