collaborators

7 papers

cs.IR2026

VirtualMLE: A Virtual ML Engineer that Optimizes Sequential Recommenders

Shiteng Cao, Jingwen Liu, Junda She +1

Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning, reflection, and tool utilization, unlocking new paradigms for automating…

cs.IR2026

Coarse-to-Fine Long-term Interest Modeling for Generative Recommendation

Shiteng Cao, Junda She, Ji Liu +9

Leveraging long-term user behavioral patterns is a key trajectory for enhancing the accuracy of modern recommender systems. While generative recommender systems have emerged as a t…

cs.IR2026

OpenOneRec Technical Report

Guorui Zhou, Honghui Bao, Jiaming Huang +44

While the OneRec series has successfully unified the fragmented recommendation pipeline into an end-to-end generative framework, a significant gap remains between recommendation sy…

cs.IR2026

ALPBench: A Benchmark for Attribution-level Long-term Personal Behavior Understanding

Lu Ren, Junda She, Xinchen Luo +23

Recent advances in large language models have highlighted their potential for personalized recommendation, where accurately capturing user preferences remains a key challenge. Leve…

cs.IR2026

Unleashing the Native Recommendation Potential: LLM-Based Generative Recommendation via Structured Term Identifiers

Zhiyang Zhang, Junda She, Kuo Cai +8

Leveraging the vast open-world knowledge and understanding capabilities of Large Language Models (LLMs) to develop general-purpose, semantically-aware recommender systems has emerg…

cs.IR2025

OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service

Zhipeng Wei, Kuo Cai, Junda She +8

Local life service is a vital scenario in Kuaishou App, where video recommendation is intrinsically linked with store's location information. Thus, recommendation in our scenario i…