3 accepted papers
Personalization plays a critical role in numerous language tasks and applications, since users with the same requirements may prefer diverse outputs based on their interests. This has led to the development of various personalized approaches aimed at adapting large language models (LLMs) to generate…
Recommender systems are among the most impactful AI applications, interacting with billions of users every day, guiding them to relevant products, services, or information tailored to their preferences. However, the research and development of recommender systems are hindered by existing datasets th…
Conversational search utilizes muli-turn natural language contexts to retrieve relevant passages. Existing conversational dense retrieval models mostly view a conversation as a fixed sequence of questions and responses, overlooking the severe data sparsity problem – that is, users can perform a conv…