Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation
Paper • 2605.01284 • Published • 1
Datasets:
Dataset Viewer
The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code: ConfigNamesError
Exception: TypeError
Message: Value.__init__() missing 1 required positional argument: 'dtype'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1182, in dataset_module_factory
).get_module()
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 690, in get_module
config_name: DatasetInfo.from_dict(dataset_info_dict)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 284, in from_dict
return cls(**{k: v for k, v in dataset_info_dict.items() if k in field_names})
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<string>", line 20, in __init__
File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 170, in __post_init__
self.features = Features.from_dict(self.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1983, in from_dict
obj = generate_from_dict(dic)
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1564, in generate_from_dict
return {key: generate_from_dict(value) for key, value in obj.items()}
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1583, in generate_from_dict
return class_type(**{k: v for k, v in obj.items() if k in field_names})
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Value.__init__() missing 1 required positional argument: 'dtype'Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Wiki-CoE
Wiki-CoE is a multimodal question-answering dataset for evaluating whether a model can answer questions from visual evidence and produce an explicit chain of evidence. Each example pairs a natural-language question with one or more Wikipedia page screenshots and asks the model to return both the answer and the supporting evidence.
The dataset is intended for research on visual reasoning, evidence localization, and chain-of-evidence style multimodal QA.
Dataset contents
The main release is under release_strict_chainsplit_20260428_1338/:
| File | Description |
|---|---|
train.json |
training split, 35,210 examples |
test.json |
test split, 35,208 examples |
val_1000_seed42.json |
small validation subset, 1,000 examples |
split_report.json |
high-level split statistics |
val_1000_seed42_manifest.json |
validation subset indices |
Each example contains:
| Field | Description |
|---|---|
question |
input question |
answer |
short answer |
type |
reasoning type |
num_hops |
number of evidence hops |
evidence_chain |
ordered evidence screenshots, bounding boxes, and sub-questions |
evidences |
supporting evidence metadata |
Screenshot archive
The screenshot images are stored as a split archive under release_assets/.
To reconstruct the image directory:
cat release_assets/screenshots_trimmed.tar.zst.part-* > screenshots_trimmed.tar.zst
tar --use-compress-program=unzstd -xf screenshots_trimmed.tar.zst
This creates:
screenshots_trimmed/
The archive contains 76,000 PNG screenshots. SHA256 checksums for the archive parts are provided in release_assets/screenshots_trimmed.tar.zst.sha256.
Related resources
- Homepage: https://lpy.pxsec.cn
- Paper: https://arxiv.org/abs/2605.01284
- Code: https://github.com/PeiYangLiu/CoE
- Wiki-CoE model checkpoint: https://huggingface.co/PeiyangLiu/CoE-Wiki-CoE-8B
- SlideVQA model checkpoint: https://huggingface.co/PeiyangLiu/CoE-SlideVQA-8B
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