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--- |
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language: |
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- en |
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license: apache-2.0 |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- question-answering |
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- visual-question-answering |
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pretty_name: Geoperception |
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tags: |
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- multi-modal-qa |
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- math-qa |
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- figure-qa |
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- geometry-qa |
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- math-word-problem |
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- vqa |
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- geometry-reasoning |
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- numeric-common-sense |
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- scientific-reasoning |
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- logical-reasoning |
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- geometry-diagram |
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- synthetic-scene |
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- scientific-figure |
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- function-plot |
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- abstract-scene |
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- mathematics |
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dataset_info: |
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features: |
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- name: id |
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dtype: string |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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- name: predicate |
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dtype: string |
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- name: image |
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dtype: image |
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splits: |
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- name: train |
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num_bytes: 2515310.0 |
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num_examples: 100 |
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download_size: 1108727 |
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dataset_size: 2515310.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# Dataset Card for Geoperception |
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A Benchmark for Low-level Geometric Perception |
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## Dataset Details |
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### Dataset Description |
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Geoperception is sourced from the Geometry-3K corpus, which offers precise logical forms for geometric diagrams, compiled from popular high-school textbooks. |
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### Dataset Sources |
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- **Repository:** [https://github.com/euclid-multimodal/Euclid-Model] |
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- **Paper:** [More Information Needed] |
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- **Demo:** [More Information Needed] |
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## Uses |
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Evaluation of multimodal LLM's ability of low-level visual perception in 2D geometry domain. |
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## Dataset Structure |
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### Fields |
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[More Information Needed] |
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## Citation |
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**BibTeX:** |
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[More Information Needed] |
