Ruiyang Ren

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 5 papers; trusts 327 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 534 citations into it; #19,833 of 35,345 by trust here, #4,722 by citations
• Natural Language Processing — 234 citations into it
• Computer Vision and Pattern Recognition — 201 citations into it; #16,359 of 21,575 by trust here, #6,737 by citations
• Information Retrieval & Search — 176 citations into it; #770 of 1,022 by trust here, #279 by citations
• Large Language Models — 145 citations into it
• Information Systems — 89 citations into it
• Evaluation & Benchmarks — 80 citations into it
• Representation & Self-Supervised Learning — 35 citations into it

Whom Ruiyang Ren trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Rodrigo Nogueira
4. Yoshua Bengio
5. Kyunghyun Cho
6. Ilya Sutskever
7. Jimmy Ba
8. Alex Krizhevsky
9. Kaiming He
10. Kenton C. T. Lee

Who trusts Ruiyang Ren overall

1. Wayne Xin Zhao
2. Keshav Santhanam
3. Zhuyun Dai
4. Jing Liu
5. Haejun Lee
6. Omar Khattab
7. Liang Wang
8. Vincent Y. Zhao
9. Luyu Gao
10. Hong-Liu Cao

Papers from Ruiyang Ren's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Gradient-based learning applied to document recognition
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering (2020) — 749 citations
• A Survey of Large Language Models (2023) — 4,706 citations
• PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval (2021) — 103 citations
• RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking (2021) — 307 citations
• Dense Text Retrieval Based on Pretrained Language Models: A Survey (2022) — 325 citations