Datasets:
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README.md
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---
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<a href='https://next-gpt.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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<a href='https://arxiv.org/pdf/2401.10727'><img src='https://img.shields.io/badge/Paper-PDF-orange'></a>
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<a href='https://arxiv.org/pdf/2401.10727'><img src='https://img.shields.io/badge/Arxiv-Page-purple'></a>
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<a href="https://huggingface.co/collections/tianzhechu/sftvsrl-models-and-data-6797ba6de522c7de7fcb80ba"><img src='https://img.shields.io/badge/Data-HuggingFace-red'></a>
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# Dataset Card for All-Angles Bench
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<!-- Provide a quick summary of the dataset. -->
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This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
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## Dataset Details
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### Dataset Description
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<!-- Provide a longer summary of what this dataset is. -->
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- **Curated by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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### Dataset Sources
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<!-- Provide the basic links for the dataset. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset("ch-chenyu/All-Angles-Bench")
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```
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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[More Information Needed]
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## Citation
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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```bibtex
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@article{yeh2025seeing,
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title={Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs},
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author={Chun-Hsiao Yeh, Chenyu Wang, Shengbang Tong, Ta-Ying Cheng, Rouyu Wang, Tianzhe Chu, Yuexiang Zhai, Yubei Chen, Shenghua Gao and Yi Ma},
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journal={arXiv preprint arXiv:2401.10727},
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year={2025}
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}
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```
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