Pei Ke

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 8 papers; trusts 149 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 247 citations into it
• Natural Language Processing — 184 citations into it
• Computer Vision and Pattern Recognition — 81 citations into it
• Large Language Models — 80 citations into it
• Evaluation & Benchmarks — 45 citations into it
• Prompting & Reasoning — 18 citations into it
• Model Architectures — 17 citations into it
• Optimization & Training — 17 citations into it

Whom Pei Ke trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alec Radford
5. Ilya Sutskever
6. Yann LeCun
7. Alex Krizhevsky
8. Alex Graves
9. Sepp Hochreiter
10. Richard Socher

Who trusts Pei Ke overall

1. Yuxian Gu
2. Jiaxu Zhao
3. Hanqing Zhang
4. Chenguang Zhu
5. W. Yu

Papers from Pei Ke's perspective

Ordered by how strongly the researchers Pei Ke 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. Gradient-based learning applied to document recognition
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

• Language Generation with Multi-hop Reasoning on Commonsense Knowledge Graph (2020) — 120 citations
• CPM-2: Large-scale Cost-effective Pre-trained Language Models (2021) — 101 citations
• CPM: A Large-scale Generative Chinese Pre-trained Language Model (2020) — 132 citations
• EVA2.0: Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training (2022) — 60 citations
• CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation (2022) — 45 citations
• EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training (2021) — 58 citations
• A Large-Scale Chinese Short-Text Conversation Dataset (2020) — 151 citations
• SentiLARE: Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis (2019) — 80 citations