Woojeong Jin

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 6 papers; trusts 286 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 163 citations into it
• Computer Vision and Pattern Recognition — 92 citations into it
• Natural Language Processing — 55 citations into it
• Multimodal Learning — 33 citations into it
• Information Systems — 29 citations into it
• Graph Learning — 28 citations into it
• Evaluation & Benchmarks — 27 citations into it
• Representation & Self-Supervised Learning — 27 citations into it

Whom Woojeong Jin trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kyunghyun Cho
6. Ilya Sutskever
7. Kaiming He
8. Dzmitry Bahdanau
9. Yann LeCun
10. Oriol Vinyals

Who trusts Woojeong Jin overall

1. Lingfeng Zhong
2. Shaoxiong Ji
3. Anthony Meng Huat Tiong
4. Oscar Mañas
5. Yaru Hao
6. K. Liang
7. Sanjay Subramanian
8. Junnan Li
9. Xiaolong Jin
10. Shirui Pan

Papers from Woojeong Jin's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data (2020) — 60 citations
• Recurrent Event Network for Reasoning over Temporal Knowledge Graphs (2019) — 63 citations
• Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer (2022) — 13 citations
• A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models (2021) — 176 citations
• Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs (2019) — 493 citations
• Jointly Learning Explainable Rules for Recommendation with Knowledge Graph (2019) — 246 citations