Haibo Ding

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 78 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 106 citations into it
• Natural Language Processing — 78 citations into it
• Computer Vision and Pattern Recognition — 44 citations into it
• Large Language Models — 34 citations into it
• Information Retrieval & Search — 31 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Haibo Ding trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Kaiming He
4. Yann LeCun
5. Diederik P. Kingma
6. Ilya Sutskever
7. Alex Krizhevsky
8. Jacob Devlin
9. Alex Graves
10. Tomas Mikolov

Papers from Haibo Ding's perspective

Ordered by how strongly the researchers Haibo Ding 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

• How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering (2020) — 594 citations
• X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models (2020) — 165 citations
• Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer (2022) — 53 citations