Sohee Yang
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 5 papers; trusts 245 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 164 citations into it; #16,342 of 35,345 by trust here, #20,377 by citations
- Natural Language Processing — 85 citations into it
- Computer Vision and Pattern Recognition — 70 citations into it; #10,435 of 21,575 by trust here, #15,529 by citations
- Large Language Models — 44 citations into it
- Information Retrieval & Search — 27 citations into it; #506 of 1,022 by trust here, #793 by citations
- Evaluation & Benchmarks — 26 citations into it
- Retrieval-Augmented Generation — 11 citations into it
- Efficiency & Compression — 9 citations into it
Whom Sohee Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Sewon Min
- Alex Krizhevsky
- Ilya Sutskever
- Danqi Chen
- Oriol Vinyals
- Kaiming He
- Yann LeCun
Who trusts Sohee Yang overall
- Gautier Izacard
- Zhengbao Jiang
- Mathilde Caron
- Lucas Hosseini
- Sebastian Riedel
- Barlas Oğuz
- Edouard Grave
- Luyu Gao
- Patrick Lewis
- Jinhyuk Lee
Papers from Sohee Yang's perspective
Ordered by how strongly the researchers Sohee Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Is Retriever Merely an Approximator of Reader? (2020) — 44 citations
- Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation (2019) — 18 citations
- TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models (2022) — 137 citations
- Knowledge Unlearning for Mitigating Privacy Risks in Language Models (2022) — 490 citations
- Towards Continual Knowledge Learning of Language Models (2021) — 210 citations