1 citations · 1 across the 3 of their papers we have counts for
5 papers
MetaRTL: Meta-path Attention Enhanced Relational Table Learning
Ken Zhong, Weichen Li, Zheng Wang
Relational table learning has gained increasing attention with the widespread use of relational databases. Existing methods typically rely on deep GNN or HGNN stacks, leading to hi…
InRTL: Effective Intra-Inter Interaction Learning for Relational Tables
Weichen Li, Ken Zhong, Zheng Wang +2
Relational table learning has recently emerged as an important research direction for modeling multiple tables connected through primary key-foreign key (PK-FK) relationships. Desp…
LakeMLB: Data Lake Machine Learning Benchmark
Feiyu Pan, Tianbin Zhang, Aoqian Zhang +5
Data lakes have become a fundamental platform for large-scale machine learning by enabling flexible management of heterogeneous data. Despite their growing importance, standardized…
TLSQL: Table Learning Structured Query Language
Feiyang Chen, Ken Zhong, Aoqian Zhang +3
Table learning has recently emerged as an important paradigm at the intersection of database systems and machine learning. However, applying table learning in practice often requir…
rLLM: Relational Table Learning with LLMs
Weichen Li, Xiaotong Huang, Jianwu Zheng +4
We introduce rLLM (relationLLM), a PyTorch library designed for Relational Table Learning (RTL) with Large Language Models (LLMs). The core idea is to decompose state-of-the-art Gr…