8 papers
MemoryCD: Benchmarking Long-Context User Memory of LLM Agents for Lifelong Cross-Domain Personalization
Weizhi Zhang, Xiaokai Wei, Wei-Chieh Huang +4
Recent advancements in Large Language Models (LLMs) have expanded context windows to million-token scales, yet benchmarks for evaluating memory remain limited to short-session synt…
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…
Rotate Both Ways: Time-and-Order RoPE for Generative Recommendation
Xiaokai Wei, Jiajun Wu, Daiyao Yi +2
Generative recommenders, typically transformer-based autoregressive models, predict the next item or action from a user's interaction history. Their effectiveness depends on how th…
The Layout Is the Model: On Action-Item Coupling in Generative Recommendation
Xiaokai Wei, Jiajun Wu, Daiyao Yi +2
Generative Recommendation (GR) models treat a user's interaction history as a sequence to be autoregressively predicted. When both items and actions (e.g., watch time, purchase, co…
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…
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…
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…