1 citations · 1 across the 5 of their papers we have counts for
5 papers
SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks
Xiangyi Li, Yimin Liu, Wenbo Chen +75
Agent Skills are structured packages of procedural knowledge that augment large language model (LLM) agents at inference time. Despite rapid adoption, there is no standard way to m…
Declarative Data Pipeline for Large Scale ML Services
Yunzhao Yang, Runhui Wang, Xuanqing Liu +14
Modern distributed data processing systems struggle to balance performance, maintainability, and developer productivity when integrating machine learning at scale. These challenges…
CSR-Bench: Benchmarking LLM Agents in Deployment of Computer Science Research Repositories
Yijia Xiao, Runhui Wang, Luyang Kong +2
The increasing complexity of computer science research projects demands more effective tools for deploying code repositories. Large Language Models (LLMs), such as Anthropic Claude…
GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security
Xuanqing Liu, Luyang Kong, Runhui Wang +5
Schema matching constitutes a pivotal phase in the data ingestion process for contemporary database systems. Its objective is to discern pairwise similarities between two sets of a…
Neural Locality Sensitive Hashing for Entity Blocking
Runhui Wang, Luyang Kong, Yefan Tao +6
Locality-sensitive hashing (LSH) is a fundamental algorithmic technique widely employed in large-scale data processing applications, such as nearest-neighbor search, entity resolut…