[Academic Paper] Pre-training on Multi-modal for Improved Persona Detection Using Multi Datasets

Abstract: Persona identification helps AI-based communication systems provide personalized and situationally informed interactions. This paper introduces pre-training on CNN, BERT, and GPT models to improve persona detection on PMPC and ROCStories datasets. Two speakers with different personalities have dialogues in the PMPC dataset. The challenge is to match each speaker to their persona. The ROCStories dataset contains fictional character traits and activities. Our study uses transformer-based design to improve persona detection using ROCStories dataset external context. We compare our method to leading models in the field. We found that pre-training and fine-tuning on several datasets improves model performance. External context from tale collections may improve persona detection algorithms and help understand human personality and behavior. Our study found that pre-training CNN, BERT, and GPT models improves persona detection, improving user experiences and communication. The method could be used in chatbots, personalized recommendation systems, and customer support. Additionally, it can help create AI-driven communication systems with tailored, context-aware, and human-like interactions.

Lay summary (by Claude 3 Sonnet): Researchers have developed a new method to help artificial intelligence (AI) systems better understand and communicate with different personalities. They used machine learning techniques to train AI models on datasets containing stories and dialogues between characters with distinct personalities. By pre-training the AI models on this data first, and then fine-tuning them on specific tasks, the researchers were able to significantly improve the AI’s ability to accurately identify a person’s personality from their words and actions. This technology could be useful for creating more natural and personalized interactions with AI assistants, chatbots, recommendation systems, and other AI-driven communication tools. Instead of giving the same generic responses, these AI systems could tailor their language and behavior to each individual user’s unique personality and preferences.