Fangzhao Wu

Artificial Intelligence · 2015–2023

A researcher in the Science corpus: 14 papers; trusts 208 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 279 citations into it; #11,843 of 35,345 by trust here, #8,706 by citations
• Information Systems — 114 citations into it; #3,482 of 8,771 by trust here, #1,740 by citations
• Computer Vision and Pattern Recognition — 71 citations into it
• Natural Language Processing — 65 citations into it
• Large Language Models — 58 citations into it
• Recommender Systems — 37 citations into it
• Management Science and Operations Research — 26 citations into it
• Optimization & Training — 24 citations into it

Whom Fangzhao Wu trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Jeffrey Pennington
6. Jimmy Ba
7. Richard Socher
8. Ilya Sutskever
9. Ruslan Salakhutdinov
10. Robert Tibshirani

Who trusts Fangzhao Wu overall

1. Chuhan Wu
2. Yu Zhang
3. Xilun Chen
4. Tao Qi
5. Jialu Liu
6. Qiang Yang
7. Claire Cardie
8. Yongfeng Huang
9. Fajie Yuan
10. Niklas Muennighoff

Papers from Fangzhao Wu's perspective

Ordered by how strongly the researchers Fangzhao Wu 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. ImageNet classification with deep convolutional neural networks
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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Neural News Recommendation with Long- and Short-term User Representations (2019) — 326 citations
• Benchmarking and Defending against Indirect Prompt Injection Attacks on Large Language Models (2023) — 305 citations
• Defending ChatGPT against jailbreak attack via self-reminders (2023) — 472 citations
• Communication-efficient federated learning via knowledge distillation (2021) — 593 citations
• A federated graph neural network framework for privacy-preserving personalization (2021) — 328 citations
• FedNER: Medical Named Entity Recognition with Federated Learning (2020) — 23 citations
• FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning (2020) — 67 citations
• FedRec: Privacy-Preserving News Recommendation with Federated Learning (2020) — 18 citations
• DA-Transformer: Distance-aware Transformer (2020) — 49 citations
• MIND: A Large-scale Dataset for News Recommendation (2020) — 670 citations
• Neural News Recommendation with Multi-Head Self-Attention (2019) — 366 citations
• NPA: Neural News Recommendation with Personalized Attention (2019) — 367 citations
• Neural News Recommendation with Attentive Multi-View Learning (2019) — 337 citations
• Collaborative Multi-domain Sentiment Classification (2015) — 57 citations