6 citations · 7 across the 5 of their papers we have counts for
5 papers
OMuleT: Orchestrating Multiple Tools for Practicable Conversational Recommendation
Se-eun Yoon, Xiaokai Wei, Yexi Jiang +5
In this paper, we present a systematic effort to design, evaluate, and implement a realistic conversational recommender system (CRS). The objective of our system is to allow users…
Forecasting Live Chat Intent from Browsing History
Se-eun Yoon, Ahmad Bin Rabiah, Zaid Alibadi +2
Customers reach out to online live chat agents with various intents, such as asking about product details or requesting a return. In this paper, we propose the problem of predictin…
Calibration-Disentangled Learning and Relevance-Prioritized Reranking for Calibrated Sequential Recommendation
Hyunsik Jeon, Se-eun Yoon, Julian McAuley
Calibrated recommendation, which aims to maintain personalized proportions of categories within recommendations, is crucial in practical scenarios since it enhances user satisfacti…
Imagery as Inquiry: Exploring A Multimodal Dataset for Conversational Recommendation
Se-eun Yoon, Hyunsik Jeon, Julian McAuley
We introduce a multimodal dataset where users express preferences through images. These images encompass a broad spectrum of visual expressions ranging from landscapes to artistic…
Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation
Se-eun Yoon, Zhankui He, Jessica Maria Echterhoff +1
Synthetic users are cost-effective proxies for real users in the evaluation of conversational recommender systems. Large language models show promise in simulating human-like behav…