Sungju Kim

Artificial Intelligence · 2021–2024

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 136 citations into it
• Large Language Models — 60 citations into it
• Information Systems — 56 citations into it

Whom Sungju Kim trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Michael R Douglas

Papers from Sungju Kim's perspective

Ordered by how strongly the researchers Sungju Kim trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Decoupled Weight Decay Regularization
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Training language models to follow instructions with human feedback (Neural Information Processing Systems)
10. SQuAD: 100,000+ Questions for Machine Comprehension of Text

Their papers

• What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers (2021) — 134 citations
• A Survey on Large Language Models for Code Generation (2024) — 1,059 citations