Fuli Feng's Homepage
Wenjie Wang's Homepage
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The boom of generative models has paved the way for significant advances in recommender systems. For instance, pre-trained generative models offer unprecedented opportunities to improve recommender algorithms for user modeling. This workshop aims to provide a platform for researchers to actively explore and share innovative ideas on integrating generative models into recommender systems, mainly focusing on five key aspects: i) enhancing recommender algorithms, ii)generating personalized content in some scen
Donald Biggar Willett Professor in Engineering University of Illinois at Urbana-Champaign (UIUC)
Abstract Recent years have seen great success of large language models (LLMs) in performing many natural language processing tasks, especially tasks that directly serve users such as question answering, text summarization, and text generation in general. At the same time, concerns such as trustworthiness and halluciation have also raised problems about such models in terms of their actual utility when deployed in applications that serve many users. In this talk, I will systematically examine the opportuniti
Fuli Feng's Homepage
Wenjie Wang's Homepage