Jihan Yang
Artificial Intelligence · 2018–2025
A researcher in the Science corpus: 5 papers; trusts 497 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 193 citations into it; #17,905 of 35,345 by trust here, #11,327 by citations
- Computer Vision and Pattern Recognition — 177 citations into it; #11,286 of 21,575 by trust here, #11,498 by citations
- Large Language Models — 52 citations into it
- Representation & Self-Supervised Learning — 41 citations into it
- Model Architectures — 10 citations into it
- Optimization & Training — 9 citations into it
- Radiology, Nuclear Medicine and Imaging — 9 citations into it; #1,231 of 3,265 by trust here, #1,970 by citations
- Signal Processing — 7 citations into it
Whom Jihan Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Yoshua Bengio
- Ross B. Girshick
- Yann LeCun
- Ilya Sutskever
- Alec Radford
- Christian Szegedy
Who trusts Jihan Yang overall
Papers from Jihan Yang's perspective
Ordered by how strongly the researchers Jihan Yang 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation (2018) — 574 citations
- Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs (2024) — 900 citations
- SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training (2025) — 649 citations
- Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces (2024) — 669 citations
- ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection (2021) — 240 citations