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README.md
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license: apache-2.0
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---
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数据集文件元信息以及数据文件,请浏览“数据集文件”页面获取。
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pretty_name: Wiki-CoE
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language:
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- en
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license: apache-2.0
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task_categories:
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- question-answering
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- visual-question-answering
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tags:
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- multimodal
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- visual-question-answering
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- chain-of-evidence
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- document-understanding
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- wiki
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size_categories:
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- 10K<n<100K
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# Wiki-CoE
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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.
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The dataset is intended for research on visual reasoning, evidence localization, and chain-of-evidence style multimodal QA.
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## Dataset contents
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The main release is under `release_strict_chainsplit_20260428_1338/`:
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| File | Description |
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|---|---:|
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| `train.json` | training split, 35,210 examples |
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| `test.json` | test split, 35,208 examples |
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| `val_1000_seed42.json` | small validation subset, 1,000 examples |
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| `split_report.json` | high-level split statistics |
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| `val_1000_seed42_manifest.json` | validation subset indices |
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Each example contains:
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| Field | Description |
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|---|---|
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| `question` | input question |
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| `answer` | short answer |
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| `type` | reasoning type |
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| `num_hops` | number of evidence hops |
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| `evidence_chain` | ordered evidence screenshots, bounding boxes, and sub-questions |
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| `evidences` | supporting evidence metadata |
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## Screenshot archive
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The screenshot images are stored as a split archive under `release_assets/`.
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To reconstruct the image directory:
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```bash
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cat release_assets/screenshots_trimmed.tar.zst.part-* > screenshots_trimmed.tar.zst
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tar --use-compress-program=unzstd -xf screenshots_trimmed.tar.zst
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```
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This creates:
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```text
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screenshots_trimmed/
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```
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The archive contains 76,000 PNG screenshots. SHA256 checksums for the archive parts are provided in `release_assets/screenshots_trimmed.tar.zst.sha256`.
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## Related resources
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- Code: https://github.com/PeiYangLiu/CoE
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- Wiki-CoE model checkpoint: https://huggingface.co/PeiyangLiu/CoE-Wiki-CoE-8B
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- SlideVQA model checkpoint: https://huggingface.co/PeiyangLiu/CoE-SlideVQA-8B
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