Dataset for Large Language Models Classification of Astronomical Transient : Survey Images, Labels, and Zooniverse Results

This dataset supports the study on the application of Large Language Models (LLMs) to astronomical transient classification. It contains data from three wide-field optical surveys: Pan-STARRS, MeerLICHT, and ATLAS, and includes the following components:

1. Survey Image Files

   • Image triplets (New, Reference, and Difference images) for each transient candidate in the three datasets.
   • Images are organized by survey (Pan-STARRS, MeerLICHT, and ATLAS).

2. Survey Label Files

   • Ground-truth classification labels for each candidate in the three surveys.
   • Labels include categories such as Real (e.g., transients and variable stars for MeerLICHT, and only explosive transients for Pan-STARRS and ATLAS) and Bogus (various types of artifacts), as determined by professional astronomers.

3. Zooniverse Classification Results

   • Results from the Zooniverse campaign evaluating the quality of Gemini’s outputs.
   • Includes responses from professional astronomers who rated the coherence of Gemini's classifications and explanations on a 0–5 scale.

Purpose:

The dataset is intended for researchers interested in exploring:

• The use of LLMs for transient classification.
• Ground-truth labels and their application in astronomical classification tasks.
• Human evaluation of AI-generated outputs in astronomy.

Use and Citation:

Please cite this dataset using the DOI provided by Zenodo if used in your research. For details on the methodology, refer to the associated publication: "Large Language Models Enable Textual Interpretation of Image-Based Astronomical Transient Classifications", Under Review, 2025