Adversarial Prompt and Annotated Image Dataset for Bias Analysis in Text-to-Image Models

Paper 1: Towards an Adversarial-Attack Approach to Assess Bias in Text-to-Image Models

This dataset accompanies the paper and includes the following resources:

biased-prompts-list.xlsx – List of all biased prompts used for image generation.

generated-images.zip – Archive containing all generated image files.

annotated-images-dataset.xlsx – Spreadsheet with annotations for each generated image.

GPT-4 Log Execution-Annotation.docx – Log of GPT-4 executions showing the annotation process and corresponding outputs.

spreadsheets-for-results-analysis.zip – Folder containing the spreadsheets used for quantitative results analysis.

The associated Jupyter Notebooks (available at https://github.com/ufal-waterloo/biased-prompts) provide scripts to:

Annotate images automatically using GPT.

Generate images via Hugging Face API calls using the prompt lists.

Explore the annotated dataset to compute bias-related metrics across gender and skin tone.

All required files from this dataset (prompt lists, generation scripts, and annotated datasets) should be placed inside the resources/ folder in the github repository to execute the notebooks properly.