Large Language Models as Data Augmenters for Cold-Start Item Recommendation

no code implementations • 18 Feb 2024 • Jianling Wang, Haokai Lu, James Caverlee, Ed Chi, Minmin Chen

The reasoning and generalization capabilities of LLMs can help us better understand user preferences and item characteristics, offering exciting prospects to enhance recommendation systems.

Recommendation Systems

Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation

no code implementations • 2 Jun 2023 • Jianling Wang, Haokai Lu, Sai Zhang, Bart Locanthi, HaoTing Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen

The multi-funnel setup effectively balances between coverage and relevance.

Long-Term Value of Exploration: Measurements, Findings and Algorithms

no code implementations • 12 May 2023 • Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen

We conduct live experiments on one of the largest short-form video recommendation platforms that serves billions of users to validate the new experiment designs, quantify the long-term values of exploration, and to verify the effectiveness of the adopted neural linear bandit algorithm for exploration.

Recommendation Systems