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dataset_info:
features:
- name: conference
dtype: string
- name: year
dtype: int32
- name: paper_id
dtype: int32
- name: title
dtype: string
- name: abstract
dtype: string
- name: topics
sequence: string
- name: image_url
dtype: string
splits:
- name: train
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
dataset_size: 24321079
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
# POSTERSUM Dataset
## Dataset Summary
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).
## Dataset Details
### Data Fields
Each record in the dataset contains the following fields:
- `conference` (*string*): Name of the conference where the research poster was presented (e.g., ICLR, ICML, NeurIPS).
- `year` (*int*): The year of the conference.
- `paper_id` (*int*): Conference identifier for the research paper associated with the poster.
- `title` (*string*): The title of the research paper.
- `abstract` (*string*): The human-written abstract of the paper, serving as the ground-truth summary for the poster.
- `topics` (*list of strings*): Machine learning topics related to the research (e.g., Reinforcement Learning, Natural Language Processing, Graph Neural Networks).
- `image_url` (*string*): URL to the image file of the scientific poster.
### Dataset Statistics
- **Total number of poster-summary pairs:** 16,305
- **Total number of unique topics:** 137
- **Average summary length:** 224 tokens
- **Train/Validation/Test split:** 10,305 / 3,000 / 3,000
## Citation
```
@misc{saxena2025postersummultimodalbenchmarkscientific,
title={PosterSum: A Multimodal Benchmark for Scientific Poster Summarization},
author={Rohit Saxena and Pasquale Minervini and Frank Keller},
year={2025},
eprint={2502.17540},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2502.17540},
}
``` |