5 citations · 9 across the 4 of their papers we have counts for
5 papers
RelServe: Fast LLM Inference Serving on Relational Data
Xin Zhang, Shihong Gao, Yanyan Shen +2
The use of Large Language Models (LLMs) for querying relational data has given rise to relQuery, a workload pattern that applies templated LLM calls to structured tables. As relQue…
Momentum-integrated Multi-task Stock Recommendation with Converge-based Optimization
Hao Wang, Jingshu Peng, Yanyan Shen +4
Stock recommendation is critical in Fintech applications, which leverage price series and alternative information to estimate future stock performance. Traditional time-series fore…
A Framework for Elastic Adaptation of User Multiple Intents in Sequential Recommendation
Zhikai Wang, Yanyan Shen
Recently, substantial research has been conducted on sequential recommendation, with the objective of forecasting the subsequent item by leveraging a user's historical sequence of…
Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving
Shihong Gao, Xin Zhang, Yanyan Shen +1
Large language model (LLM) inference serving systems are essential to various LLM-based applications. As demand for LLM services continues to grow, scaling these systems to handle…
Improving the End-to-End Efficiency of Offline Inference for Multi-LLM Applications Based on Sampling and Simulation
Jingzhi Fang, Yanyan Shen, Yue Wang +1
As large language models (LLMs) have shown great success in many tasks, they are used in various applications. While a lot of works have focused on the efficiency of single-LLM app…