Jingjing Xu

Artificial Intelligence · 2018–2023

A researcher in the Science corpus: 10 papers; trusts 318 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 270 citations into it
• Natural Language Processing — 159 citations into it
• Computer Vision and Pattern Recognition — 127 citations into it
• Large Language Models — 66 citations into it
• Evaluation & Benchmarks — 35 citations into it
• Model Architectures — 35 citations into it
• Generative Models — 29 citations into it
• Information Systems — 18 citations into it

Whom Jingjing Xu trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Dzmitry Bahdanau
5. Ronald J. Williams
6. Diederik P. Kingma
7. Yann LeCun
8. Alex Krizhevsky
9. Kaiming He
10. Jiwei Li

Who trusts Jingjing Xu overall

1. Chenze Shao
2. Serra Sinem Tekiroğlu
3. Quang Pham
4. Stanislau Semeniuta
5. Wei-Jen Ko
6. Kalpesh Krishna
7. Zhiqiang Hu
8. Akhilesh Sudhakar
9. Xu Sun
10. Pengcheng Yang

Papers from Jingjing Xu's perspective

Ordered by how strongly the researchers Jingjing Xu 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (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

• Diversity-Promoting GAN: A Cross-Entropy Based Generative Adversarial Network for Diversified Text Generation (2018) — 152 citations
• Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach (2018) — 215 citations
• Reasoning Over Semantic-Level Graph for Fact Checking (2019) — 186 citations
• Asking Clarification Questions in Knowledge-Based Question Answering (2019) — 80 citations
• MTG: A Benchmark Suite for Multilingual Text Generation (2021) — 26 citations
• Vocabulary Learning via Optimal Transport for Neural Machine Translation (2020) — 104 citations
• A Survey on In-context Learning (2022) — 1,101 citations
• Can We Edit Factual Knowledge by In-Context Learning? (2023) — 356 citations
• Understanding and Improving Layer Normalization (2019) — 543 citations
• DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text (2018) — 70 citations