Long Ouyang
Impact in
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- Artificial Intelligence in Healthcare and Education
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- Topic Modeling
- Adversarial Robustness in Machine Learning
- Reinforcement Learning in Robotics
- Natural Language Processing Techniques
Papers in
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- Categorization, perception, and language 3
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- Reading and Literacy Development 2
- Language Development and Disorders 2
- Co-authors
- Peter Welinder (1 shared paper)Ryan Lowe (1 shared paper)Sandhini Agarwal (1 shared paper)Paul F. Christiano (1 shared paper)Carroll L. Wainwright (1 shared paper)Pamela Mishkin (1 shared paper)John Schulman (1 shared paper)Amanda Askell (1 shared paper)
- Journals
- Cognitive Science (3 papers)ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL) (1 paper)neural information processing systems (1 paper)
- Partner nations
- United StatesSwedenUnited Kingdom
In The Last Decade
Long Ouyang
5 papers receiving 139 citations
Peers
Comparison fields: 5 of 46
- Health Informatics 10
- Artificial Intelligence 70
- Safety Research 11
- Computer Vision and Pattern Recognition 17
- Information Systems 18
Countries citing papers authored by Long Ouyang
This map shows the geographic impact of Long Ouyang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Long Ouyang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Ouyang more than expected).
Fields of papers citing papers by Long Ouyang
This network shows the impact of papers produced by Long Ouyang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Long Ouyang. The network helps show where Long Ouyang may publish in the future.
Co-authors
The 17 scholars most cited alongside Long Ouyang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 126 | |
| 2 | 2016 | 11 | |
| 3 | 2016 | 5 | |
| 4 | Semantic Coherence Facilitates Distributional Learning of Word Meanings | 2012 | 2 |
| 5 | webppl-oed: A practical optimal experiment design system. | 2018 | 2 |
About Long Ouyang
Long Ouyang is a scholar working on Experimental and Cognitive Psychology, Developmental and Educational Psychology, Artificial Intelligence, Management Science and Operations Research and Nuclear Energy and Engineering, having authored 5 papers that have together received 146 indexed citations. Recurring topics across this work include Categorization, perception, and language (3 papers), Reading and Literacy Development (2 papers), Bayesian Modeling and Causal Inference (2 papers), Language Development and Disorders (2 papers), Data Analysis with R (1 paper), Logic, programming, and type systems (1 paper), Topic Modeling (1 paper) and Optimal Experimental Design Methods (1 paper). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (70 citations), Safety Research (11 citations), Computer Vision and Pattern Recognition (17 citations) and Information Systems (18 citations). Long Ouyang has collaborated with scholars based in United States, Sweden and United Kingdom. Frequent co-authors include Peter Welinder, Ryan Lowe, Sandhini Agarwal, Paul F. Christiano, Carroll L. Wainwright, Pamela Mishkin, John Schulman, Amanda Askell, Jan Leike and Jacob Hilton. Their work appears in journals such as Cognitive Science, ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL) and neural information processing systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.