Hi! Your wonderful literature may help researchers have a comprehensive overview of recent advances.
You may have a look at our recently released paper at WSDM 2021.
The neural state machine introduced in this paper is an easy-to-use GNN approach to reason on KB (directed relational graphs) and also show promising results on benchmarks (2nd place for CWQ on the leaderboard).
Paper title:
Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
The link to our paper is:
https://arxiv.org/abs/2101.03737
We also release the code:
https://github.com/RichardHGL/WSDM2021_NSM
Hi! Your wonderful literature may help researchers have a comprehensive overview of recent advances.
You may have a look at our recently released paper at WSDM 2021. The neural state machine introduced in this paper is an easy-to-use GNN approach to reason on KB (directed relational graphs) and also show promising results on benchmarks (2nd place for CWQ on the leaderboard). Paper title: Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals The link to our paper is: https://arxiv.org/abs/2101.03737 We also release the code: https://github.com/RichardHGL/WSDM2021_NSM