6 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.IR2024★ 6 cited
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…
cs.CL2024★ 1 cited
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…