Jing Ma

Artificial Intelligence · with Luo · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 246 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 68 citations into it
• Computer Vision and Pattern Recognition — 49 citations into it
• Multimodal Learning — 32 citations into it
• Large Language Models — 29 citations into it
• Natural Language Processing — 19 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Jing Ma trusts overall

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

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

Papers from Jing Ma's perspective

Ordered by how strongly the researchers Jing Ma 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. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Microsoft COCO: Common Objects in Context

Their papers

• WizardCoder: Empowering Code Large Language Models with Evol-Instruct (2023) — 1,012 citations
• VC-GPT: Visual Conditioned GPT for End-to-End Generative Vision-and-Language Pre-training (2022) — 22 citations