Zhenfang Chen

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 6 papers; trusts 516 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 208 citations into it
• Computer Vision and Pattern Recognition — 180 citations into it
• Multimodal Learning — 68 citations into it
• Natural Language Processing — 60 citations into it
• Large Language Models — 48 citations into it
• Prompting & Reasoning — 26 citations into it
• Reinforcement Learning — 24 citations into it
• Model Architectures — 22 citations into it

Whom Zhenfang Chen trusts overall

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

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

Who trusts Zhenfang Chen overall

1. Yining Hong
2. Mingyu Ding
3. Bo Wu
4. Zirui Zhao

Papers from Zhenfang Chen's perspective

Ordered by how strongly the researchers Zhenfang Chen 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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• 3D-LLM: Injecting the 3D World into Large Language Models (2023) — 599 citations
• Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning (2021) — 107 citations
• Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision (2023) — 457 citations
• Planning with Large Language Models for Code Generation (2023) — 256 citations
• See, Think, Confirm: Interactive Prompting Between Vision and Language Models for Knowledge-based Visual Reasoning (2023) — 57 citations
• Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (2021) — 86 citations