Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About
About me
Posts
Black Magic of LaTeX for Limited Spaces
Published:
전문연구요원 보충역 논산 육군훈련소 2022 후기 (준비물 및 팁)
Published:
Three Basic Tips for PyTorch Beginners
Published:
Use a Docker Container like a Remote Server
Published:
A Short History of Positional Encoding
Published:
Note: I am still writing this post.
Blogs and Newsletters about Machine Learning
Published:
Install PyTorch with CUDA 10.0
Published:
publications
Homogeneity-Based Transmissive Process To Model True and False News in Social Networks
Jooyeon Kim, Dongkwan Kim, and Alice Oh. International Conference on Web Search and Data Mining (WSDM), 2019
Additive Compositionality of Word Vectors
Yeon Seonwoo, Sungjoon Park, Dongkwan Kim, and Alice Oh. Workshop on Noisy User-generated Text at EMNLP (EMNLP W-NUT), 2019
Supervised Graph Attention Network for Semi-Supervised Node Classification
Dongkwan Kim and Alice Oh. Workshop on Graph Representation Learning at NeurIPS (NeurIPS GRL), 2019
Note: The full version is published at ICLR 2021.
How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim and Alice Oh. International Conference on Learning Representations (ICLR), 2021
One-sentence Summary: We propose a method that self-supervise graph attention through edges and it should be designed according to the average degree and homophily of graphs.
Efficient Representation Learning of Subgraphs by Subgraph-To-Node Translation
Dongkwan Kim and Alice Oh. Workshop on Geometrical and Topological Representation Learning at ICLR (ICLR GTRL), 2022
One-sentence Summary: We propose Subgraph-To-Node translation to efficiently learn representations of subgraphs by coarsely translating subgraphs into nodes.
Models and Benchmarks for Representation Learning of Partially Observed Subgraphs
Dongkwan Kim, Jiho Jin, Jaimeen Ahn and Alice Oh. International Conference on Information and Knowledge Management (CIKM, Short Papers Track), 2022
Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
Dongkwan Kim and Alice Oh. International Conference on Machine Learning (ICML), 2024
One-sentence Summary: We propose Subgraph-To-Node translation to effectively and efficiently learn representations of subgraphs by coarsely translating subgraphs into nodes.
Generalizing Weisfeiler-Lehman Kernels to Subgraphs
Dongkwan Kim and Alice Oh. Arxiv, 2024
One-sentence Summary: We propose WLKS that extends the WL graph kernel to subgraphs, captures high-order structural similarities in k-hop neighborhoods, efficiently outperforming state-of-the-art GNNs.
Perceptions to Beliefs: Exploring Precursory Inferences for Theory of Mind in Large Language Models
Chani Jung, Dongkwan Kim, Jiho Jin, Jiseon Kim, Yeon Seonwoo, Yejin Choi, Alice Oh, and Hyunwoo Kim. Empirical Methods in Natural Language Processing (EMNLP), 2024
One-sentence Summary: We assess key precursors of Theory of Mind (ToM) in LLMs by perception-augmented ToM benchmarks. We propose PercepToM, a ToM method inspired by our findings of models’ strength in perception inference and weakness in perception-to-belief inference.
Salad-Bowl-LLM: Multi-Culture LLMs by In-Context Demonstrations from Diverse Cultures
Dongkwan Kim, Junho Myung, and Alice Oh. Workshop on Socially Responsible Language Modelling Research at NeurIPS (NeurIPS SoLaR), 2024
One-sentence Summary: We explore the use of in-context learning with diverse demonstrations to enhance Large Language Models’ cultural understanding.