task_categories:visual-question-answering language:en license:mit size_categories:n<1K format:parquet modality:image modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: user_profile
    dtype: string
  - name: question
    dtype: string
  - name: answer_gpt4o
    dtype: string
  - name: answer_gpt4o_1paragraph
    dtype: string
  - name: answer_gpt4o_1sentence
    dtype: string
  splits:
  - name: train
    num_bytes: 3613200
    num_examples: 144
  download_size: 3490003
  dataset_size: 3613200
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: mit
task_categories:
- visual-question-answering
language:
- en
size_categories:
- n<1K
---
## VLM Benchmark for Domain-Specefic Evaluation
To assess the personalization capabilities of the proposed model compared to the baseline, we employed this benchmark:

- **ElderlyTech-VQA Bench**: Comprising **144 triplets** of images, questions, and answers, this benchmark focuses on real-world technology-related queries from elderly individuals. The questions are provided to us by Assistance publique Hôpitaux de Paris (APHP) and the images, sourced from **FairFace**, ensure diversity in ethnicity and gender. Reference answers were generated using **GPT-4o** with detailed instructions to provide high-quality responses.

## Citation
If you use this dataset in your research, please cite the original sources:

```bibtex

@article{rahimi2025user,
  title={User-VLM: LLM Contextualization with Multimodal Pre-trained User Models},
  author={Rahimi, Hamed and Abrini, Mouad and Khoramshahi, Mahdi and Chetouani, Mohamed},
  year={2025}
}

@article{rahimi2025user,
  title={User-VLM 360°: Personalized Vision Language Models with User-aware Tuning for Social Human-Robot Interactions},
  author={Rahimi, Hamed and Bhaj, Adil, and Abrini, Mouad and Khoramshahi, Mahdi and Ghogho, Mounir and Chetouani, Mohamed},
  year={2025}
}

```

## License
This dataset is licensed under the MIT License.

## Contact
For any questions or issues regarding the dataset, please open an issue on this repository or contact the dataset maintainers.