Cheng Li

Artificial Intelligence · with Bendersky · 2004–2023

A researcher in the Science corpus: 7 papers; trusts 66 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 137 citations into it
• Natural Language Processing — 62 citations into it
• Computer Vision and Pattern Recognition — 44 citations into it
• Information Systems — 42 citations into it
• Information Retrieval & Search — 32 citations into it
• Large Language Models — 25 citations into it
• Model Architectures — 21 citations into it
• Evaluation & Benchmarks — 16 citations into it

Whom Cheng Li trusts overall

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

1. Chengxiang Zhai
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Tomas Mikolov
5. Yann LeCun
6. Sepp Hochreiter
7. Alex Krizhevsky
8. Ilya Sutskever
9. Robert Krovetz
10. Diederik P. Kingma

Who trusts Cheng Li overall

1. Alexandra Olteanu
2. Jia Wang
3. Qi Cao
4. Jiezhong Qiu
5. Vincent Wenchen Zheng
6. Carlos Castillo
7. Huawei Shen

Papers from Cheng Li's perspective

Ordered by how strongly the researchers Cheng Li trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023) — 354 citations
• Two supervised learning approaches for name disambiguation in author citations (2004) — 410 citations
• Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching (2020) — 13 citations
• Semantic Text Matching for Long-Form Documents (2019) — 102 citations
• TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank (2018) — 146 citations
• DeepCas: An End-to-end Predictor of Information Cascades (2016) — 378 citations
• ReQ-ReC: high recall retrieval with query pooling and interactive classification (2014) — 52 citations