Generative Dialogue

Generative dialogue research focuses on creating models that can engage in natural, coherent, and informative conversations. Current efforts concentrate on improving model performance in complex reasoning tasks through techniques like retrieval-augmented generation and chain-of-thought prompting, as well as enhancing data efficiency via methods such as pseudo-data generation and data augmentation. These advancements aim to build more robust and versatile dialogue systems, impacting fields like language learning, customer service, and human-computer interaction by providing more engaging and helpful conversational agents.