most citedOpenOneRec Technical Report

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.IR20251 cited

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.CV2025

Kwai Keye-VL 1.5 Technical Report

Biao Yang, Bin Wen, Boyang Ding +58

In recent years, the development of Large Language Models (LLMs) has significantly advanced, extending their capabilities to multimodal tasks through Multimodal Large Language Mode…

cs.IR2025

OneRec-V2 Technical Report

Guorui Zhou, Hengrui Hu, Hongtao Cheng +72

Recent breakthroughs in generative AI have transformed recommender systems through end-to-end generation. OneRec reformulates recommendation as an autoregressive generation task, a…

cs.CV2025

Kwai Keye-VL Technical Report

Kwai Keye Team, Biao Yang, Bin Wen +57

While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities on static images, they often fall short in comprehending dynamic, information-dense short-form vi…

cs.IR2025

OneRec Technical Report

Guorui Zhou, Jiaxin Deng, Jinghao Zhang +62

Recommender systems have been widely used in various large-scale user-oriented platforms for many years. However, compared to the rapid developments in the AI community, recommenda…

cs.IR2024

QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou

Xinchen Luo, Jiangxia Cao, Tianyu Sun +17

In recent years, with the significant evolution of multi-modal large models, many recommender researchers realized the potential of multi-modal information for user interest modeli…