Hoyeop Lee — accepted AI-conference papers

2024

iGraphMix: Input Graph Mixup Method for Node Classification

Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim +1

ICLR 2024poster

Recently, Input Mixup, which augments virtual samples by interpolating input features and corresponding labels, is one of the promising methods to alleviate the over-fitting problem on various domains including image classification and natural language processing because of its ability to generate a…

Cited by 5 Source ↗PDF ↗Scholar ↗

2021

Self-Supervised Multimodal Opinion Summarization

Jinbae Im, Moonki Kim, Hoyeop Lee, Hyunsouk Cho, Sehee Chung

ACL 2021long

Recently, opinion summarization, which is the generation of a summary from multiple reviews, has been conducted in a self-supervised manner by considering a sampled review as a pseudo summary. However, non-text data such as image and metadata related to reviews have been considered less often. To us…

Cited by 39 Source ↗PDF ↗code ↗Scholar ↗