Jingtao Zhan

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 5 papers; trusts 72 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 77 citations into it; #21,347 of 35,345 by trust here, #15,542 by citations
• Information Retrieval & Search — 72 citations into it
• Computer Vision and Pattern Recognition — 39 citations into it
• Information Systems — 31 citations into it
• Natural Language Processing — 30 citations into it
• Large Language Models — 21 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Jingtao Zhan trusts overall

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

1. Zhuyun Dai
2. Rodrigo Nogueira
3. Diederik P. Kingma
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Kyunghyun Cho
7. Stephen E. Robertson
8. Jamie Callan
9. Alex Krizhevsky
10. Kaiming He

Who trusts Jingtao Zhan overall

1. Wayne Xin Zhao
2. Keshav Santhanam
3. Jing Liu
4. Omar Khattab
5. Jiaxin Mao
6. Ruiyang Ren
7. Sebastian Hofstätter
8. Shengyao Zhuang
9. Yiqun Liu
10. Ji-rong Wen

Papers from Jingtao Zhan's perspective

Ordered by how strongly the researchers Jingtao Zhan 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. 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
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

• Optimizing Dense Retrieval Model Training with Hard Negatives (2021) — 352 citations
• Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance (2021) — 97 citations
• An Analysis of BERT in Document Ranking (2020) — 55 citations
• Leveraging Passage-level Cumulative Gain for Document Ranking (2020) — 40 citations
• RepBERT: Contextualized Text Embeddings for First-Stage Retrieval (2020) — 140 citations