Soon-gyo Jung
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 82 citations into it; #28,489 of 35,345 by trust here, #15,236 by citations
- Natural Language Processing — 50 citations into it
- Information Systems — 39 citations into it; #6,877 of 8,771 by trust here, #3,198 by citations
- Communication — 32 citations into it; #2,459 of 3,460 by trust here, #1,044 by citations
- Safety, Robustness & Interpretability — 26 citations into it
- Signal Processing — 5 citations into it
Whom Soon-gyo Jung trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zeerak Talat
- Mainack Mondal
- Ji Ho Park
- Bradley Efron
- Hossein Hosseini
- Diederik P. Kingma
- Paula Fortuna
- K. Gwet
Who trusts Soon-gyo Jung overall
Papers from Soon-gyo Jung's perspective
Ordered by how strongly the researchers Soon-gyo Jung trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- Efficient Estimation of Word Representations in Vector Space
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Detecting Hate Speech on the World Wide Web
- Long Short-Term Memory
- Distributed Representations of Sentences and Documents
Their papers
- Developing an online hate classifier for multiple social media platforms (2020) — 268 citations
- Online Hate Interpretation Varies by Country, But More by Individual: A Statistical Analysis Using Crowdsourced Ratings (2018) — 46 citations
- Online Hate Ratings Vary by Extremes: A Statistical Analysis (2019) — 55 citations
- Anatomy of Online Hate: Developing a Taxonomy and Machine Learning Models for Identifying and Classifying Hate in Online News Media (2018) — 190 citations