1.5k citations · 5.2k across the 138 of their papers we have counts for
144 papers
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems
Xiaocong Chen, Siyu Wang, Julian McAuley +2
Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significa…
Large Language Models as Zero-Shot Conversational Recommenders
Zhankui He, Zhouhang Xie, Rahul Jha +6
In this paper, we present empirical studies on conversational recommendation tasks using representative large language models in a zero-shot setting with three primary contribution…
Learning Concise and Descriptive Attributes for Visual Recognition
An Yan, Yu Wang, Yiwu Zhong +6
Recent advances in foundation models present new opportunities for interpretable visual recognition -- one can first query Large Language Models (LLMs) to obtain a set of attribute…
Reinforcement Learning for Generative AI: A Survey
Yuanjiang Cao, Quan Z. Sheng, Julian McAuley +1
Deep Generative AI has been a long-standing essential topic in the machine learning community, which can impact a number of application areas like text generation and computer visi…
Comparing Apples to Apples: Generating Aspect-Aware Comparative Sentences from User Reviews
Jessica Echterhoff, An Yan, Julian McAuley
It is time-consuming to find the best product among many similar alternatives. Comparative sentences can help to contrast one item from others in a way that highlights important fe…
CLIPSonic: Text-to-Audio Synthesis with Unlabeled Videos and Pretrained Language-Vision Models
Hao-Wen Dong, Xiaoyu Liu, Jordi Pons +5
Recent work has studied text-to-audio synthesis using large amounts of paired text-audio data. However, audio recordings with high-quality text annotations can be difficult to acqu…