Dialog System
Dialog systems aim to create natural and effective communication between humans and machines, focusing on achieving specific goals (task-oriented) or engaging in open-ended conversations. Current research emphasizes improving memory management in multi-session dialogues, enhancing model efficiency and accuracy through techniques like reinforcement learning and data augmentation, and addressing challenges like data scarcity and bias in training data. These advancements are crucial for building more robust, engaging, and helpful dialog systems with applications ranging from customer service and language learning to assistive technologies and medical applications.
Papers
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