Qingru Zhang
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 3 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 59 citations into it
- Computer Vision and Pattern Recognition — 28 citations into it
- Large Language Models — 24 citations into it
- Natural Language Processing — 23 citations into it
- Efficiency & Compression — 16 citations into it
- Optimization & Training — 14 citations into it
- Evaluation & Benchmarks — 7 citations into it
Whom Qingru Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Jimmy Ba
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Pranav Rajpurkar
- Yann LeCun
- Ilya Loshchilov
Who trusts Qingru Zhang overall
Papers from Qingru Zhang's perspective
Ordered by how strongly the researchers Qingru Zhang 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
- Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (2023) — 729 citations
- AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (2023) — 404 citations
- AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods (2018) — 73 citations