Here are some photos from the event:

SemEval is an authoritative international series of workshops and NLP (Natural Language Processing) evaluation exercises. In Task 13C, we had to classify the authorship of source code into 4 classes: Human, AI, Hybrid, and Adversarial AI.

Our Solution: For this task, we developed a Multi-Modal Ensemble that performs an in-depth analysis of the source code from three different perspectives:

1. Code Semantics - Utilizing the UniXcoder language model through Multiple Instance Learning (MIL) to properly handle long files.
2. Textual Patterns - Employing our MazgaBERT model to highlight structural and textual writing patterns.
3. Statistical Anomalies - Using classic XGBoost trained on hand-crafted features derived from stylistic and structural properties of the code.

Our System Paper with a detailed description of the solution will be presented at the SemEval workshop and subsequently published in the official ACL Anthology. More updates to come!