Publications (9)
Learning from Natural Language Explanations for Generalizable Entity Matching
Somin Wadhwa, Adit Krishnan, Runhui Wang +2
Entity matching is the task of linking records from different sources that refer to the same real-world entity. Past work has primarily treated entity linking as a standard supervi…
Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries
Sibo Wang, Renchi Yang, Runhui Wang +5
Given a graph , a source node and a target node , the personalized PageRank (PPR) of with respect to is the probability that a random walk starting from termi…
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…
Language is All a Graph Needs
Ruosong Ye, Caiqi Zhang, Runhui Wang +2
The emergence of large-scale pre-trained language models has revolutionized various AI research domains. Transformers-based Large Language Models (LLMs) have gradually replaced CNN…
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…
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…
Sudowoodo: Contrastive Self-supervised Learning for Multi-purpose Data Integration and Preparation
Runhui Wang, Yuliang Li, Jin Wang
Machine learning (ML) is playing an increasingly important role in data management tasks, particularly in Data Integration and Preparation (DI&P). The success of ML-based approache…
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…