Yung-Sung Chuang

Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 5 papers; trusts 114 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 131 citations into it; #27,696 of 35,345 by trust here, #9,870 by citations
• Natural Language Processing — 50 citations into it; #4,585 of 5,688 by trust here, #4,449 by citations
• Signal Processing — 43 citations into it
• Computer Vision and Pattern Recognition — 42 citations into it; #17,098 of 21,575 by trust here, #15,529 by citations
• Speech & Audio — 38 citations into it
• Large Language Models — 23 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Meta & Continual Learning — 8 citations into it; #867 of 1,041 by trust here, #848 by citations

Whom Yung-Sung Chuang trusts overall

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

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

Who trusts Yung-Sung Chuang overall

1. Zixuan Ke
2. Yanzhe Zhang
3. Xisen Jin
4. Ying Zhao
5. Chengyu Wang
6. B. Ermiş
7. Xuezhi Wang
8. Lasse Borgholt
9. Yijia Shao
10. Xu Han

Papers from Yung-Sung Chuang's perspective

Ordered by how strongly the researchers Yung-Sung Chuang 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• SUPERB: Speech processing Universal PERformance Benchmark (2021) — 1,225 citations
• SpeechBERT: An Audio-and-Text Jointly Learned Language Model for End-to-End Spoken Question Answering (2019) — 108 citations
• Semi-Supervised Spoken Language Understanding via Self-Supervised Speech and Language Model Pretraining (2020) — 65 citations
• DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models (2023) — 397 citations
• Lifelong Language Knowledge Distillation (2020) — 57 citations