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Exception: SplitsNotFoundError Message: The split names could not be parsed from the dataset config. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 153, in compute compute_split_names_from_info_response( File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 125, in compute_split_names_from_info_response config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config) File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 590, in get_previous_step_or_raise raise CachedArtifactError( libcommon.simple_cache.CachedArtifactError: The previous step failed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info for split_generator in builder._split_generators( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 88, in _split_generators raise ValueError( ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response for split in get_dataset_split_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names info = get_dataset_config_info( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, in get_dataset_config_info raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.
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DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models
paper link: DocGenome
We present DocGenome, a structured document dataset constructed by annotating 500K scientific documents from 153 disciplines in the arXiv open-access community, using our custom auto-labeling pipeline DocParser. DocGenome features four characteristics:
- Completeness: It is the first dataset to structure data from all modalities including 13 layout attributes along with their \LaTeX\ source codes.
- Logicality: It provides 6 logical relationships between different entities within each scientific document.
- Diversity: It covers various document-oriented tasks, including document classification, visual grounding, document layout detection, document transformation, open-ended single-page QA and multi-page QA.
- Correctness: It undergoes rigorous quality control checks conducted by a specialized team.
Highlight:
- Data quality rating: for each structured document in DocGenome shown here
- Tutorials on how to use the DocGenome dataset.
- TestSet downloads from Huggingface. If you want to evaluate your model on TestSet, please refer to Evaluation.
DocGenome Benchmark Introduction
Datasets | # Discipline | # Category of Units | # Pages in Train-set | # Pages in Test-set | # Task | # Used Metric | Publication | Entity Relations |
---|---|---|---|---|---|---|---|---|
DocVQA | - | N/A | 11K | 1K | 1 | 2 | 1960-2000 | ❎ |
DocLayNet | - | 11 | 80K | 8K | 1 | 1 | - | ❎ |
DocBank | - | 13 | 0.45M | 50K | 3 | 1 | 2014-2018 | ❎ |
PubLayNet | - | 5 | 0.34M | 12K | 1 | 1 | - | ❎ |
VRDU | - | 10 | 7K | 3K | 3 | 1 | - | ❎ |
DUDE | - | N/A | 20K | 6K | 3 | 3 | 1860-2022 | ❎ |
D^4LA | - | 27 | 8K | 2K | 1 | 3 | - | ❎ |
Fox Benchmark | - | 5 | N/A (No train-set) | 0.2K | 3 | 5 | - | ❎ |
ArXivCap | 32 | N/A | 6.4M* | N/A | 4 | 3 | - | ❎ |
DocGenome (ours) | 153 | 13 | 6.8M | 9K | 7 | 7 | 2007-2022 | ✅ |
Definition of relationships between component units
DocGenome contains 4 level relation types and 2 cite relation types, as shown in the following table:
Name | Description | Example |
---|---|---|
Identical | Two blocks share the same source code. | Cross-column text; Cross-page text. |
Title adjacent | The two titles are adjacent. | (\section{introduction}, \section{method}) |
Subordinate | One block is a subclass of another block. | (\section{introduction}, paragraph within Introduction) |
Non-title adjacent | The two text or equation blocks are adjacent. | (Paragraph 1, Paragraph 2) |
Explicitly-referred | One block refers to another block via footnote, reference, etc. | (As shown in \ref{Fig: 5} ..., Figure 5) |
Implicitly-referred | The caption block refers to the corresponding float environment. | (Table Caption 1, Table 1) |
Attribute of component units
DocGenome has 13 attributes of component units, which can be categorized into two classes
- 1) Fixed-form units, including Text, Title, Abstract, etc., which are characterized by sequential reading and hierarchical relationships readily discernible from the list obtained in Stage-two of the designed DocParser.
- 2) Floating-form units, including Table, Figure, etc., which establish directional references to fixed-form units through commands like \texttt{\textbackslash ref} and \texttt{\textbackslash label}.
Index | Category | Notes |
---|---|---|
0 | Algorithm | |
1 | Caption | Titles of Images, Tables, and Algorithms |
2 | Equation | |
3 | Figure | |
4 | Footnote | |
5 | List | |
7 | Table | |
8 | Text | |
9 | Text-EQ | Text block with inline equations |
10 | Title | Section titles |
12 | PaperTitle | |
13 | Code | |
14 | Abstract |
Citation
If you find our work useful in your research, please consider citing Fox:
@article{xia2024docgenome,
title={DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models},
author={Xia, Renqiu and Mao, Song and Yan, Xiangchao and Zhou, Hongbin and Zhang, Bo and Peng, Haoyang and Pi, Jiahao and Fu, Daocheng and Wu, Wenjie and Ye, Hancheng and others},
journal={arXiv preprint arXiv:2406.11633},
year={2024}
}
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