|
--- |
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dataset_info: |
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features: |
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- name: conference |
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dtype: string |
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- name: year |
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dtype: int32 |
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- name: paper_id |
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dtype: int32 |
|
- name: title |
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dtype: string |
|
- name: abstract |
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dtype: string |
|
- name: topics |
|
sequence: string |
|
- name: image_url |
|
dtype: string |
|
splits: |
|
- name: train |
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num_bytes: 15394703 |
|
num_examples: 10305 |
|
- name: validation |
|
num_bytes: 4461536 |
|
num_examples: 3000 |
|
- name: test |
|
num_bytes: 4464840 |
|
num_examples: 3000 |
|
download_size: 12550503 |
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dataset_size: 24321079 |
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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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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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--- |
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|
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# POSTERSUM Dataset |
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## Dataset Summary |
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The **POSTERSUM** dataset is a multimodal benchmark designed for the summarization of scientific posters into research paper abstracts. The dataset consists of **16,305** research posters collected from major machine learning conferences, including ICLR, ICML, and NeurIPS, spanning the years **2022-2024**. Each poster is provided in image format along with its corresponding abstract as a summary. This dataset is intended for research in multimodal understanding and summarization tasks, particularly in vision-language models (VLMs) and Multimodal Large Language Models (MLLMs). |
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## Dataset Details |
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### Data Fields |
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Each record in the dataset contains the following fields: |
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- `conference` (*string*): Name of the conference where the research poster was presented (e.g., ICLR, ICML, NeurIPS). |
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- `year` (*int*): The year of the conference. |
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- `paper_id` (*int*): Conference identifier for the research paper associated with the poster. |
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- `title` (*string*): The title of the research paper. |
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- `abstract` (*string*): The human-written abstract of the paper, serving as the ground-truth summary for the poster. |
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- `topics` (*list of strings*): Machine learning topics related to the research (e.g., Reinforcement Learning, Natural Language Processing, Graph Neural Networks). |
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- `image_url` (*string*): URL to the image file of the scientific poster. |
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### Dataset Statistics |
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- **Total number of poster-summary pairs:** 16,305 |
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- **Total number of unique topics:** 137 |
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- **Average summary length:** 224 tokens |
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- **Train/Validation/Test split:** 10,305 / 3,000 / 3,000 |
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## Citation |
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``` |
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@misc{saxena2025postersummultimodalbenchmarkscientific, |
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title={PosterSum: A Multimodal Benchmark for Scientific Poster Summarization}, |
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author={Rohit Saxena and Pasquale Minervini and Frank Keller}, |
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year={2025}, |
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eprint={2502.17540}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2502.17540}, |
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} |
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``` |