8 papers
WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture
Renqin Cai, Dawei Sun, Yuanjun Yao +8
As scalability becomes increasingly important in recommendation modeling, recent architectures have advanced the modeling of two broad sources of ranking signals along separate pat…
Bumblebee: Interleaved Mixed-Layer Building Blocks for Large-Scale Recommendation Systems
David Bauer, Cancan Zhang, Wenshun Liu +11
Recommendation systems have undergone significant transformations in the past years. The transition from traditional feature interaction modules to generative next-action predictio…
FAB-Bench: A Framework for Adaptive RAG Benchmarking in Semiconductor Manufacturing
Jingbin Qian, Congwen Yi, Min Xia +3
Retrieval-Augmented Generation (RAG) has become critical for knowledge-intensive applications, yet evaluating its performance in vertical domains remains difficult due to domain co…
Bending the Scaling Law Curve in Large-Scale Recommendation Systems
Qin Ding, Kevin Course, Linjian Ma +19
Learning from user interaction history through sequential models has become a cornerstone of large-scale recommender systems. Recent advances in large language models have revealed…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
Target-Aware Early Stage Ranking
Juhee Hong, Meng Liu, Shengzhi Wang +18
Early Stage Ranking (ESR) in large-scale recommendation systems is dominated by ''user--item decoupling'' Two Tower architectures, which scale efficiently but cannot capture fine-g…