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The advent of generative Large Language Models (LLMs) such as ChatGPT hascatalyzed transformative advancements across multiple domains. However,alongside these advancements, they have also introduced potential threats. Onecritical concern is the misuse of LLMs by disinformation spreaders, leveragingthese models to generate highly persuasive yet misleading content thatchallenges the disinformation detection system. This work aims to address thisissue by answering three research questions: (1) To what extent can the currentdisinformation detection technique reliably detect LLM-generateddisinformation? (2) If traditional techniques prove less effective, can LLMsthemself be exploited to serve as a robust defense against advanceddisinformation? and, (3) Should both these strategies falter, what novelapproaches can be proposed to counter this burgeoning threat effectively? Aholistic exploration for the formation and detection of disinformation isconducted to foster this line of research.

Disinformation Detection: An Evolving Challenge in the Age of LLMs