Linyang Li

Artificial Intelligence · with Zhang · 2018–2024

A researcher in the Science corpus: 6 papers; trusts 173 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 101 citations into it; #33,032 of 35,345 by trust here, #13,163 by citations
• Natural Language Processing — 70 citations into it
• Computer Vision and Pattern Recognition — 37 citations into it
• Safety, Robustness & Interpretability — 33 citations into it
• Signal Processing — 17 citations into it
• Large Language Models — 15 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Linyang Li trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Ian J. Goodfellow
5. Alex Krizhevsky
6. Yann LeCun
7. Ilya Sutskever
8. Jacob Devlin
9. Kaiming He
10. Richard Socher

Who trusts Linyang Li overall

1. Xipeng Qiu
2. Alexis Ross
3. Chenglei Si
4. Dong Wang
5. Xu Han
6. John X. Morris
7. Zhengyan Zhang
8. Ning Ding
9. Shiqi Wang
10. Ana Marasovic

Papers from Linyang Li's perspective

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

Their papers

• BERT-ATTACK: Adversarial Attack against BERT Using BERT (2020) — 900 citations
• Character-LLM: A Trainable Agent for Role-Playing (2023) — 475 citations
• InternLM2 Technical Report (2024) — 416 citations
• Token-Aware Virtual Adversarial Training in Natural Language Understanding (2021) — 56 citations
• Generating Adversarial Examples in Chinese Texts Using Sentence-Pieces (2020) — 8 citations
• U-Net: Machine Reading Comprehension with Unanswerable Questions (2018) — 49 citations