10 citations · 17 across the 4 of their papers we have counts for
4 papers
Learning Topology-Specific Experts for Molecular Property Prediction
Su Kim, Dongha Lee, SeongKu Kang +2
Recently, graph neural networks (GNNs) have been successfully applied to predicting molecular properties, which is one of the most classical cheminformatics tasks with various appl…
Ask Me What You Need: Product Retrieval using Knowledge from GPT-3
Su Young Kim, Hyeonjin Park, Kyuyong Shin +1
As online merchandise become more common, many studies focus on embedding-based methods where queries and products are represented in the semantic space. These methods alleviate th…
Learnable Structural Semantic Readout for Graph Classification
Dongha Lee, Su Kim, Seonghyeon Lee +2
With the great success of deep learning in various domains, graph neural networks (GNNs) also become a dominant approach to graph classification. By the help of a global readout op…
Scaling Law for Recommendation Models: Towards General-purpose User Representations
Kyuyong Shin, Hanock Kwak, Su Young Kim +4
Recent advancement of large-scale pretrained models such as BERT, GPT-3, CLIP, and Gopher, has shown astonishing achievements across various task domains. Unlike vision recognition…