23 citations · 27 across the 6 of their papers we have counts for
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cs.LG2022
An Empirical Study of Retrieval-enhanced Graph Neural Networks
Dingmin Wang, Shengchao Liu, Hanchen Wang +5
Graph Neural Networks (GNNs) are effective tools for graph representation learning. Most GNNs rely on a recursive neighborhood aggregation scheme, named message passing, thereby th…
cs.CL2022
Relational Memory Augmented Language Models
Qi Liu, Dani Yogatama, Phil Blunsom
We present a memory-augmented approach to condition an autoregressive language model on a knowledge graph. We represent the graph as a collection of relation triples and retrieve r…