Peng Qian

Artificial Intelligence · with Levy · 2016–2021

A researcher in the Science corpus: 6 papers; trusts 132 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 106 citations into it; #7,471 of 35,345 by trust here, #10,319 by citations
• Natural Language Processing — 88 citations into it; #2,308 of 5,688 by trust here, #3,332 by citations
• Model Architectures — 23 citations into it
• Representation & Self-Supervised Learning — 19 citations into it; #1,485 of 3,145 by trust here, #2,516 by citations
• Cognitive Neuroscience — 18 citations into it; #9,101 of 10,852 by trust here, #6,526 by citations
• Computer Vision and Pattern Recognition — 17 citations into it
• Evaluation & Benchmarks — 16 citations into it
• Developmental and Educational Psychology — 13 citations into it

Whom Peng Qian trusts overall

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

1. Richard Socher
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Tomas Mikolov
5. Ilya Sutskever
6. Sepp Hochreiter
7. Oriol Vinyals
8. Diederik P. Kingma
9. Alex Krizhevsky
10. Ronan Collobert

Who trusts Peng Qian overall

1. Yonatan Belinkov
2. Nadir Durrani
3. Fahim Dalvi
4. Hassan Sajjad
5. James R. Glass
6. Alex Warstadt
7. Lluís Màrquez i Villodre
8. Anthony Bau
9. Tal Linzen
10. John Hewitt

Papers from Peng Qian's perspective

Ordered by how strongly the researchers Peng Qian 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. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Structural Supervision Improves Learning of Non-Local Grammatical Dependencies (2019) — 61 citations
• A Systematic Assessment of Syntactic Generalization in Neural Language Models (2020) — 275 citations
• Investigating Language Universal and Specific Properties in Word Embeddings (2016) — 60 citations
• Neural language models as psycholinguistic subjects: Representations of syntactic state (2019) — 237 citations
• Analyzing Linguistic Knowledge in Sequential Model of Sentence (2016) — 36 citations
• What if This Modified That? Syntactic Interventions with Counterfactual Embeddings (2021) — 51 citations