1 citations · 1 across the 5 of their papers we have counts for
7 papers
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…
: Attention-Aware Accurate KV Cache Fusion for Fast Large Language Model Serving
Yuechi Zhou, Yi Su, Jianxin Zhang +5
Large language models (LLMs) have demonstrated strong capabilities in processing long contexts, enabling them to tackle tasks involving long textual inputs such as multi-turn conve…
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…
CaliDrop: KV Cache Compression with Calibration
Yi Su, Quantong Qiu, Yuechi Zhou +6
Large Language Models (LLMs) require substantial computational resources during generation. While the Key-Value (KV) cache significantly accelerates this process by storing attenti…
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…
Accurate KV Cache Quantization with Outlier Tokens Tracing
Yi Su, Yuechi Zhou, Quantong Qiu +6
The impressive capabilities of Large Language Models (LLMs) come at the cost of substantial computational resources during deployment. While KV Cache can significantly reduce recom…