Shijie Geng

Artificial Intelligence · 2020–2024

A researcher in the Science corpus: 6 papers; trusts 262 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 245 citations into it; #27,540 of 35,345 by trust here, #5,600 by citations
• Computer Vision and Pattern Recognition — 210 citations into it; #19,712 of 21,575 by trust here, #5,053 by citations
• Large Language Models — 74 citations into it
• Information Systems — 37 citations into it
• Natural Language Processing — 36 citations into it
• Model Architectures — 26 citations into it
• Recommender Systems — 10 citations into it

Whom Shijie Geng trusts overall

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

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

Who trusts Shijie Geng overall

1. Renrui Zhang
2. Yupeng Hou
3. Junjie Zhang
4. Tal Schuster
5. Junling Liu
6. Junliang Yu
7. Bowen Zheng
8. Xubin Ren
9. Shashank Rajput
10. Ruobing Xie

Papers from Shijie Geng's perspective

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

Their papers

• CLIP-Adapter: Better Vision-Language Models with Feature Adapters (2021) — 1,792 citations
• LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model (2023) — 758 citations
• SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models (2024) — 159 citations
• RomeBERT: Robust Training of Multi-Exit BERT (2021) — 32 citations
• Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5) (2022) — 915 citations
• Character Matters: Video Story Understanding with Character-Aware Relations (2020) — 11 citations