Responsible Generation of Textual and Visual Content: Addressing Hallucination, Toxicity, and Adversarial Vulnerabilities

Responsible generation of content by generative AI models is crucial for their real-world applicability. This paper investigates the practical responsible requirements of both textual and visual generative models, outlining key considerations such as generating truthful content, avoiding toxic content, refusing harmful instructions, protecting training data privacy, and ensuring generated content identifiability.