Ming Li

Artificial Intelligence · with Chen · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 172 citations into it
• Natural Language Processing — 33 citations into it
• Evaluation & Benchmarks — 22 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Ming Li trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Kaiming He
6. Ilya Sutskever
7. Jimmy Ba
8. Yann LeCun
9. Alex Graves
10. Ross B. Girshick

Who trusts Ming Li overall

1. Wei Liu

Papers from Ming Li's perspective

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

Their papers

• A Survey on Knowledge Distillation of Large Language Models (2024) — 355 citations
• From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning (2023) — 373 citations