Pat Verga

7 papers and 57 indexed citations i.

About

Pat Verga is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Pat Verga has authored 7 papers receiving a total of 57 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Pat Verga’s work include Natural Language Processing Techniques (7 papers), Topic Modeling (7 papers) and Multimodal Machine Learning Applications (4 papers). Pat Verga is often cited by papers focused on Natural Language Processing Techniques (7 papers), Topic Modeling (7 papers) and Multimodal Machine Learning Applications (4 papers). Pat Verga collaborates with scholars based in United States, Canada and Algeria. Pat Verga's co-authors include William W. Cohen, Livio Baldini Soares, Haitian Sun, Wenhu Chen, Hexiang Hu, Xi Chen, John Wieting, Yue Dong, Neha Choudhary and Andrew McCallum and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Co-authorship network of co-authors of Pat Verga i

Fields of papers citing papers by Pat Verga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pat Verga. 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 Pat Verga. The network helps show where Pat Verga may publish in the future.

Countries citing papers authored by Pat Verga

Since Specialization
Citations

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

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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2025