9 citations · 10 across the 4 of their papers we have counts for
4 papers
FuncEvalGMN: Evaluating Functional Correctness of SQL via Graph Matching Network
Yi Zhan, Yang Sun, Han Weng +7
In this paper, we propose a novel graph-based methodology to evaluate the functional correctness of SQL generation. Conventional metrics for assessing SQL code generation, such as…
Accelerating Regular Path Queries over Graph Database with Processing-in-Memory
Ruoyan Ma, Shengan Zheng, Guifeng Wang +4
Regular path queries (RPQs) in graph databases are bottlenecked by the memory wall. Emerging processing-in-memory (PIM) technologies offer a promising solution to dispatch and exec…
A new perspective on building efficient and expressive 3D equivariant graph neural networks
Weitao Du, Yuanqi Du, Limei Wang +5
Geometric deep learning enables the encoding of physical symmetries in modeling 3D objects. Despite rapid progress in encoding 3D symmetries into Graph Neural Networks (GNNs), a co…
GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation
Yongqiang Han, Likang Wu, Hao Wang +5
Sequential Recommendation is a widely studied paradigm for learning users' dynamic interests from historical interactions for predicting the next potential item. Although lots of r…