Recent literature has highlighted potential risks to academic integrity associated with large
language models (LLMs), as they can memorize parts of training instances and reproduce …

Generative models in natural language processing (NLP) have transformed machine
interactions with human language. This research offers a comparative examination of …

Generative AI (GenAI) has introduced myriad opportunities and challenges for higher
education. Anticipating this potential transformation requires understanding students' …

Text-embedding models often exhibit biases arising from the data on which they are trained.
In this paper, we examine a hitherto unexplored bias in text-embeddings: bias arising from …

The rapid advancement of Large Language Models (LLMs), such as GPT-4, has sparked
concerns regarding academic misconduct, misinformation, and the erosion of originality …

The study of the interaction between STEM education and artificial intelligence is relevant for
ensuring academic integrity because of the need to guarantee the efficacy and impartiality of …

У ході написання наукової статті було виявлено роль академічної доброчесності у
контексті її ролі у формуванні освітнього та наукового середовища, зокрема в умовах …

Анотація Для виявлення тексту, згенерованого за допомогою великих мовних моделей,
існують різні підходи, на основі яких розроблені такі алгоритми, як DetectGPT, RADAR …

Various algorithms have been developed to detect text generated by large language
models, and instruments such as DetectGPT, RADAR, Ghostbuster, GPT-Sentinel, etc. are …