Publication Date
4-2025
Presentation Length
15 minutes
College
College of Sciences & Mathematics
Department
Math and Computer Science, Department of
Student Level
Undergraduate
SPARK Category
Research
Faculty Advisor
Dr. Esteban Parra-Rodriguez
WELL Core Type
Intellectual Wellness
SPARK Session
Independent Presentation
Presentation Type
Talk/Oral
Summary
AI text generation is rapidly developing, and, as a result, it is becoming increasingly difficult to differentiate it from human written text. Our base study by Leon Fröhling et al. proposed a feature-based detection model trained on GPT2, GPT3, and Grover data, as well as human-generated text. Our work extends their research by training a modified model with four neural networks on word embeddings, select features from the original study, as well as updated data (GPT3, GPT4, and Grover).
Recommended Citation
Ahrndt, Kayla, "Extending Feature-Based Detection for Artificial Intelligence" (2025). SPARK Symposium Presentations. 67.
https://repository.belmont.edu/spark_presentations/67
