Jean Y. Wu

7.0k total citations · 1 hit paper
6 papers, 3.8k citations indexed

About

Jean Y. Wu is a scholar working on Artificial Intelligence, Social Psychology and Experimental and Cognitive Psychology. According to data from OpenAlex, Jean Y. Wu has authored 6 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 1 paper in Social Psychology and 1 paper in Experimental and Cognitive Psychology. Recurrent topics in Jean Y. Wu's work include Natural Language Processing Techniques (5 papers), Topic Modeling (5 papers) and Text and Document Classification Technologies (2 papers). Jean Y. Wu is often cited by papers focused on Natural Language Processing Techniques (5 papers), Topic Modeling (5 papers) and Text and Document Classification Technologies (2 papers). Jean Y. Wu collaborates with scholars based in United States. Jean Y. Wu's co-authors include Christopher D. Manning, Jason Chuang, Andrew Y. Ng, Christopher Potts, Richard Socher, Julie Tibshirani, Gabor Angeli, Justine Kao, Leon Bergen and Noah D. Goodman and has published in prestigious journals such as Proceedings of the National Academy of Sciences and Theory and applications of categories.

In The Last Decade

Jean Y. Wu

6 papers receiving 3.5k citations

Hit Papers

Recursive Deep Models for Semantic Compositionality Over ... 2013 2026 2017 2021 2013 1000 2.0k 3.0k

Peers

Jean Y. Wu
Comparison fields: 5 of 116
  • Artificial Intelligence 3.4k
  • Computer Vision and Pattern Recognition 477
  • Information Systems 431
  • Sociology and Political Science 208
  • Management Science and Operations Research 127
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Citations per field, relative to Jean Y. Wu
Jean Y. Wu · 1×
Citations per year, relative to Jean Y. Wu
Jean Y. Wu · 1×

Countries citing papers authored by Jean Y. Wu

Since Specialization
Citations

This map shows the geographic impact of Jean Y. Wu'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 Jean Y. Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean Y. Wu more than expected).

Fields of papers citing papers by Jean Y. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean Y. Wu. 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 Jean Y. Wu. The network helps show where Jean Y. Wu may publish in the future.

Co-authorship network of co-authors of Jean Y. Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jean Y. Wu. A scholar is included among the top collaborators of Jean Y. Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jean Y. Wu. Jean Y. Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
# Work Indexed citations
1 84
2
Stanford's Distantly Supervised Slot Filling Systems for KBP 2014
4
3
Stanford's 2014 Slot Filling Systems
10
4 85
5
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank breakdown →
3653
6
Stanford's 2013 KBP System
2

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.

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