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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: 294203058.193 |
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num_examples: 11657 |
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download_size: 93419701 |
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dataset_size: 294203058.193 |
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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 a benchmark focused specifically on accessing model's low-level visual perception ability in 2D geometry. |
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It 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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- **id** identification of each data instance |
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- **question** question |
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- **answer** answer |
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- **predicate** question type, including |
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- **PointLiesOnLine** |
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- **LineComparison** |
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- **PointLiesOnCircle** |
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- **AngleClassification** |
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- **Parallel** |
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- **Perpendicular** |
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- **Equal** |
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- **image** image |
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## Evaluation Result |
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| Model | POL | POC | ALC | LHC | PEP | PRA | EQL | Overall | |
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|--------------------------------|--------|--------|--------|--------|--------|--------|--------|---------| |
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| **Random Baseline** | 1.35 | 2.63 | **59.92** | 51.36 | 0.23 | 0.00 | 0.02 | 16.50 | |
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| **Open Source** | | | | | | | | | |
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| Molmo-7B-D | 11.96 | 35.73 | 56.77 | 16.79 | 1.06 | 0.00 | 0.81 | 17.59 | |
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| Llama-3.2-11B | 16.22 | 37.12 | 59.46 | 52.08 | 8.38 | 22.41 | 49.86 | 35.08 | |
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| Qwen2-VL-7B | 21.89 | 41.60 | 46.60 | 63.27 | 26.41 | 30.19 | 54.37 | 40.62 | |
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| Cambrian-1-8B | 15.14 | 28.68 | 58.05 | 61.48 | 22.96 | 30.74 | 31.04 | 35.44 | |
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| Pixtral-12B | 24.63 | 53.21 | 47.33 | 51.43 | 21.96 | 36.64 | 58.41 | 41.95 | |
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| **Closed Source** | | | | | | | | | |
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| GPT-4o-mini | 9.80 | 61.19 | 48.84 | 69.51 | 9.80 | 4.25 | 44.74 | 35.45 | |
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| GPT-4o | 16.43 | **71.49** | 55.63 | 74.39 | 24.80 | 60.30 | 44.69 | 49.68 | |
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| Claude 3.5 Sonnet | 25.44 | 68.34 | 42.95 | 70.73 | 21.41 | 63.92 | **66.34** | 51.30 | |
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| Gemini-1.5-Flash | **29.30** | 67.75 | 49.89 | 76.69 | 29.98 | 63.44 | 66.28 | 54.76 | |
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| Gemini-1.5-Pro | 24.42 | 69.80 | 57.96 | **79.05** | **38.81** | **76.65** | 52.15 | **56.98** | |
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## Citation |
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**BibTeX:** |
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[More Information Needed] |
