5 papers
Catalog-Native LLM: Speaking Item-ID Dialect with Less Entanglement for Recommendation
Reza Shirkavand, Xiaokai Wei, Chen Wang +3
While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reasoning, modern recommendation sys…
Toward Safe and Human-Aligned Game Conversational Recommendation via Multi-Agent Decomposition
Zheng Hui, Xiaokai Wei, Yexi Jiang +6
Conversational recommender systems (CRS) have advanced with large language models, showing strong results in domains like movies. These domains typically involve fixed content and…
Semantics Meet Signals: Dual Codebook Representationl Learning for Generative Recommendation
Zheng Hui, Xiaokai Wei, Reza Shirkavand +4
Generative recommendation has recently emerged as a powerful paradigm that unifies retrieval and generation, representing items as discrete semantic tokens and enabling flexible se…
FRONTIER-RevRec: A Large-scale Dataset for Reviewer Recommendation
Qiyao Peng, Chen Wang, Yinghui Wang +3
Reviewer recommendation is a critical task for enhancing the efficiency of academic publishing workflows. However, research in this area has been persistently hindered by the lack…
Solving the Content Gap in Roblox Game Recommendations: LLM-Based Profile Generation and Reranking
Chen Wang, Xiaokai Wei, Yexi Jiang +7
With the vast and dynamic user-generated content on Roblox, creating effective game recommendations requires a deep understanding of game content. Traditional recommendation models…