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Abstract

In the era of generative Artificial Intelligence (AI), Large Language Models (LLMs) and Vision-Language Models (VLMs), such as ChatGPT, have become double-edged swords that have revolutionized content creation but also worsened the spread of disinformation. These technologies offer impressive abilities but also raise two questions: 1. Who created this textual content, AI or human? 2. What is the underlying intent of this multimodal content? This thesis addresses each question from distinct yet complementary perspectives to advance disinformation mitigation. First, from the “authenticity” aspect: we investigate how we can identify machine-generated text algorithmically, and introduce SimMark, a semantic-based sentence-level watermarking algorithm that injects visually imperceptible yet statistically detectable patterns into the LLM-generated text based on inter-sentence semantic similarity. SimMark is model-agnostic and operates without needing access to the models’ internals. We carried out extensive experiments and found that SimMark achieves high detection rates even under various adversarial conditions such as paraphrasing attacks, while preserving text quality and fluency. Second, from the “intent” aspect: we explore the persuasive messages conveyed through internet memes—the amalgamation of textual and visual elements—to spread disinformation and influence public opinion. A core challenge in this task lies in effectively understanding the meaning expressed through the metaphorical combination of text and images in memes. We propose a novel multimodal pipeline to tackle this problem by adding an intermediate captioning step using VLMs. These detailed captions, combined with the original meme text and visual features, then feed into a multimodal, hierarchical classification model. Experimental results show our approach effectively detects persuasion techniques across multilingual and multimodal data. Together, these contributions offer tools for tracking AI-generated text and analyzing the persuasive tactics in disinformation campaigns in this new age of generative artificial intelligence.