20 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Brain (Germany)DE2 papers
- Centre Universitaire de MilaDZ1 paper
- Gwangju Institute of Science and TechnologyKR1 paper
- Hanbat National UniversityKR1 paper
- Konkuk University Medical CenterKR1 paper
- Seoul National UniversityKR1 paper
- Seoul National University of Science and TechnologyKR1 paper
- Université de MontréalCA1 paper
- University of Virginia's College at WiseUS1 paper
6 papers
BOK-VQA: Bilingual outside Knowledge-Based Visual Question Answering via Graph Representation Pretraining
Minjun Kim, Seungwoo Song, Youhan Lee +2
The current research direction in generative models, such as the recently developed GPT4, aims to find relevant knowledge information for multimodal and multilingual inputs to prov…
Neural-network quantum state study of the long-range antiferromagnetic Ising chain
Jicheol Kim, Dongkyu Kim, Dong-Hee Kim
We investigate quantum phase transitions in the transverse field Ising chain with algebraically decaying long-range (LR) antiferromagnetic interactions using the variational Monte…
Deep Context- and Relation-Aware Learning for Aspect-based Sentiment Analysis
Shinhyeok Oh, Dongyub Lee, Taesun Whang +4
Existing works for aspect-based sentiment analysis (ABSA) have adopted a unified approach, which allows the interactive relations among subtasks. However, we observe that these met…
Visual Concept Reasoning Networks
Taesup Kim, Sungwoong Kim, Yoshua Bengio
A split-transform-merge strategy has been broadly used as an architectural constraint in convolutional neural networks for visual recognition tasks. It approximates sparsely connec…
GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition
Yonghyun Kim, Wonpyo Park, Myung-Cheol Roh +1
In the field of face recognition, a model learns to distinguish millions of face images with fewer dimensional embedding features, and such vast information may not be properly enc…
Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data
Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo +1
Conventional sequential learning methods such as Recurrent Neural Networks (RNNs) focus on interactions between consecutive inputs, i.e. first-order Markovian dependency. However,…