Sarcasm Generation

Sarcasm generation research focuses on computationally creating sarcastic text and multimodal expressions (combining text and images), aiming to replicate the nuanced linguistic and visual cues that characterize human sarcasm. Current efforts involve developing sophisticated models, often incorporating multimodal mixtures of experts or semantic graph approaches, to capture the incongruity and valence reversal inherent in sarcastic communication. This field is significant for advancing natural language generation and understanding, with potential applications in areas like chatbot development and automated content creation, but faces challenges in evaluating generated sarcasm objectively and obtaining sufficient high-quality training data.