Yixuan Su
Artificial Intelligence · with Wang · 2021–2023
A researcher in the Science corpus: 4 papers; trusts 189 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 129 citations into it
- Natural Language Processing — 85 citations into it
- Computer Vision and Pattern Recognition — 81 citations into it
- Multimodal Learning — 44 citations into it
- Representation & Self-Supervised Learning — 24 citations into it
- Evaluation & Benchmarks — 20 citations into it
- Generative Models — 14 citations into it
Whom Yixuan Su trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Jimmy Ba
- Ronald J. Williams
- Alec Radford
Who trusts Yixuan Su overall
- Rohan Taori
- Hang Zhang
- Shengqiong Wu
- Kalpesh Krishna
- Zhaopeng Gu
- Tatsunori B. Hashimoto
- Hanze Dong
- Ximing Lu
- Renrui Zhang
- Jiasen Lu
Papers from Yixuan Su's perspective
Ordered by how strongly the researchers Yixuan Su trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- PandaGPT: One Model To Instruction-Follow Them All (2023) — 452 citations
- A Contrastive Framework for Neural Text Generation (2022) — 334 citations
- Language Models Can See: Plugging Visual Controls in Text Generation (2022) — 120 citations
- Plan-then-Generate: Controlled Data-to-Text Generation via Planning (2021) — 95 citations