most citedOpenOneRec Technical Report

1 citations · 1 across the 12 of their papers we have counts for

collaborators
Showing cs.IRShow all

9 papers · 1 filter

cs.IR2026

Grevo: A Unified Generative Recommendation Framework with Evolutionary Item Indexing

Huanjie Wang, Liwei Guan, Zekai Sun +2

Generative recommendation has recently emerged as a promising paradigm that reformulates retrieval as autoregressive generation over semantic identifiers (SIDs), achieving strong p…

cs.IR2026

OxygenREC-v2: Internalizing Discrimination into Generative Recommendation

Guo Tang, Hanye Wu, Changjiang Han +9

Generative recommendation unifies retrieval and ranking within a single model by autoregressively decoding semantic identifier (SID) sequences. Yet reliably incorporating behavior…

cs.IR2026

DREAM: Dynamic Refinement of Early Assignment Mappings

Liwei Guan, Huanjie Wang, Hongwei Zhang +2

Generative recommendation advances item retrieval by reformulating it as autoregressive generation of Semantic IDs (SIDs), compact token sequences that encode item semantics. While…

cs.IR2026

OneReason Technical Report

OneRec Team, Biao Yang, Boyang Ding +81

Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…

cs.IR2026

PIT: A Dynamic Personalized Item Tokenizer for End-to-End Generative Recommendation

Huanjie Wang, Xinchen Luo, Honghui Bao +6

Generative Recommendation has revolutionized recommender systems by reformulating retrieval as a sequence generation task over discrete item identifiers. Despite the progress, exis…

cs.IR2025★ 1 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.IR2025

OneRec-Think: In-Text Reasoning for Generative Recommendation

Zhanyu Liu, Shiyao Wang, Xingmei Wang +23

The powerful generative capacity of Large Language Models (LLMs) has instigated a paradigm shift in recommendation. However, existing generative models (e.g., OneRec) operate as im…

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.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…