RFBES at SemEval-2024 Task 8: Investigating Syntactic and Semantic
  Features for Distinguishing AI-Generated and Human-Written Texts
Mohammad Heydari Rad Farhan Farsi Shayan Bali Romina Etezadi Mehrnoush Shamsfard
Nowadays, the usage of Large Language Models (LLMs) has increased, and LLMs
have been used to generate texts in different languages and for different
tasks. Additionally, due to the participation of remarkable companies such as
Google and OpenAI, LLMs are now more accessible, and people can easily use
them. However, an important issue is how we can detect AI-generated texts from
human-written ones. In this article, we have investigated the problem of
AI-generated text detection from two different aspects: semantics and syntax.
Finally, we presented an AI model that can distinguish AI-generated texts from
human-written ones with high accuracy on both multilingual and monolingual
tasks using the M4 dataset. According to our results, using a semantic approach
would be more helpful for detection. However, there is a lot of room for
improvement in the syntactic approach, and it would be a good approach for
future work.