19 citations · 26 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 2 cited
Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention
Rengan Xu, Junjie Yang, Yifan Xu +17
The integration of hardware accelerators has significantly advanced the capabilities of modern recommendation systems, enabling the exploration of complex ranking paradigms previou…
cs.LG2024★ 5 cited
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Jiaqi Zhai, Lucy Liao, Xing Liu +9
Large-scale recommendation systems are characterized by their reliance on high cardinality, heterogeneous features and the need to handle tens of billions of user actions on a dail…
cs.LG2023★ 19 cited
Revisiting Neural Retrieval on Accelerators
Jiaqi Zhai, Zhaojie Gong, Yueming Wang +4
Retrieval finds a small number of relevant candidates from a large corpus for information retrieval and recommendation applications. A key component of retrieval is to model (user,…