Jinghua Piao

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 98 citations into it
• Information Systems — 68 citations into it
• Recommender Systems — 19 citations into it

Whom Jinghua Piao trusts overall

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

1. Xiangnan He
2. Steffen Rendle

Papers from Jinghua Piao's perspective

Ordered by how strongly the researchers Jinghua Piao trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Efficient Estimation of Word Representations in Vector Space
7. Language Models are Few-Shot Learners (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. Semi-Supervised Classification with Graph Convolutional Networks (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

• S3: Social-network Simulation System with Large Language Model-Empowered Agents (2023) — 331 citations
• A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions (2021) — 789 citations