Ruiqi Zhong

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 10 papers; trusts 306 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 364 citations into it; #9,197 of 35,345 by trust here, #5,495 by citations
• Natural Language Processing — 249 citations into it; #4,045 of 5,688 by trust here, #1,453 by citations
• Computer Vision and Pattern Recognition — 104 citations into it
• Large Language Models — 81 citations into it
• Information Systems — 76 citations into it; #7,504 of 8,771 by trust here, #801 by citations
• Evaluation & Benchmarks — 63 citations into it
• Prompting & Reasoning — 51 citations into it; #123 of 359 by trust here, #179 by citations
• Software — 32 citations into it; #878 of 1,227 by trust here, #130 by citations

Whom Ruiqi Zhong trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Richard Socher
4. Diederik P. Kingma
5. Yann LeCun
6. Ilya Sutskever
7. Alex Krizhevsky
8. Oriol Vinyals
9. Kaiming He
10. Alex Graves

Who trusts Ruiqi Zhong overall

1. Sewon Min
2. M. Pourreza
3. Daniel Khashabi
4. Torsten Scholak
5. Sarthak Jain
6. Hongjin Su
7. Frank F. Xu
8. Nitarshan Rajkumar
9. Luke S. Zettlemoyer
10. Haoyang Li

Papers from Ruiqi Zhong's perspective

Ordered by how strongly the researchers Ruiqi Zhong 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. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections (2021) — 188 citations
• Meta-learning via Language Model In-context Tuning (2021) — 208 citations
• UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models (2022) — 362 citations
• DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation (2022) — 563 citations
• Semantic Evaluation for Text-to-SQL with Distilled Test Suite (2020) — 190 citations
• Fine-grained Sentiment Analysis with Faithful Attention (2019) — 53 citations
• Learning by Distilling Context (2022) — 104 citations
• Semantic Scaffolds for Pseudocode-to-Code Generation (2020) — 26 citations
• InCoder: A Generative Model for Code Infilling and Synthesis (2022) — 909 citations
• Meta-tuning Language Models to Answer Prompts Better (2021) — 13 citations