Zirui Wang

Artificial Intelligence · with Zhang · 2018–2023

A researcher in the Science corpus: 11 papers; trusts 687 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 321 citations into it; #9,421 of 35,345 by trust here, #4,137 by citations
• Computer Vision and Pattern Recognition — 270 citations into it; #6,568 of 21,575 by trust here, #2,016 by citations
• Multimodal Learning — 113 citations into it; #739 of 1,211 by trust here, #256 by citations
• Natural Language Processing — 96 citations into it
• Large Language Models — 79 citations into it; #487 of 799 by trust here, #241 by citations
• Representation & Self-Supervised Learning — 62 citations into it
• Evaluation & Benchmarks — 42 citations into it
• Model Architectures — 29 citations into it

Whom Zirui Wang trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Yoshua Bengio
5. Alex Krizhevsky
6. Ilya Sutskever
7. Yann LeCun
8. Jimmy Ba
9. Ross B. Girshick
10. Alex Graves

Who trusts Zirui Wang overall

1. Wen Zhang
2. B. Ermiş
3. Zixuan Ke
4. Lingfei Deng
5. Jianfeng Wang
6. Zhengyuan Yang
7. Zhe Gan
8. Wenliang Dai
9. Wenhui Wang
10. Xiaowei Hu

Papers from Zirui Wang's perspective

Ordered by how strongly the researchers Zirui Wang 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Scaling Autoregressive Models for Content-Rich Text-to-Image Generation (2022) — 1,537 citations
• SimVLM: Simple Visual Language Model Pretraining with Weak Supervision (2021) — 965 citations
• Ferret: Refer and Ground Anything Anywhere at Any Granularity (2023) — 563 citations
• Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models (2020) — 250 citations
• Towards Zero-Label Language Learning (2021) — 115 citations
• Characterizing and Avoiding Negative Transfer (2018) — 510 citations
• Reveal: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory (2022) — 178 citations
• Towards more Reliable Transfer Learning (2018) — 12 citations
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
• Efficient Meta Lifelong-Learning with Limited Memory (2020) — 83 citations