In this session, we will introduce Pragmatic Metacognitive Prompting (PMP) as a novel approach to improve sarcasm detection in Large Language Models (LLMs). PMP leverages pragmatic reasoning and metacognitive strategies to enhance the interpretation of implied meanings and contextual cues, achieving improved performance on sarcasm detection benchmarks. This entertaining, interactive talk explains the integration of pragmatic theories into LLM prompting, offering a new direction for sentiment analysis research. It demonstrates how linguistic principles – such as implicature – influence human reasoning in complex contexts, enhancing sarcasm detection capabilities. The target audience includes AI researchers, NLP practitioners, and data scientists interested in sentiment analysis and language model enhancement. Key takeaways include understanding the application of pragmatic theories in Natural Language Processing, insights into advanced sarcasm detection methods, and practical knowledge of implementing metacognitive prompting.


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