Samuel Bowman

5.9k citations
27 papers · 3.4k indexed · 2 hit papers · h-index 14

Samuel Bowman

24 papers receiving 3.2k citations

Hit Papers

GLUE: A Multi-Task Benchmark and Analysis Platform for Na...2.4k201820262020202350010001.5k2.0k

Peers

Samuel Bowman
Comparison fields: 5 of 139
  • Artificial Intelligence 2.9k
  • Computer Vision and Pattern Recognition 860
  • Health Informatics 47
  • Computational Mathematics 9
  • General Social Sciences 48
Replace Julian Michael with:
Julian Michael United States
Ronan Le Bras United States
Shay B. Cohen United Kingdom
Baobao Chang China
Xin Jiang China
Trevor Cohn Australia
Hiroaki Hayashi Japan
Rie Johnson United States
Samuel Bowman relative to Julian Michael United States Julian Michael's profile →
Citations per field
00.5×1.5×
Julian Michael · 1×
Citations per year

Countries citing papers authored by Samuel Bowman

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Bowman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Samuel Bowman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Samuel Bowman Line = papers co-authored together Samuel Bowman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20247
3 20244
4 20230
5 20232
6 202313
7 202362
8 202222
9 202264
10 202221
11 20221
12 201820
13 201846
14 201820
15
XNLI: Evaluating Cross-lingual Sentence Representationsbreakdown →
2018499
16 201817
17 201720
18
A Gold Standard Dependency Corpus for English
2014109
19 20112
20 19874

About Samuel Bowman

Samuel Bowman is a scholar working on Artificial Intelligence, Metals and Alloys, Computer Vision and Pattern Recognition, Geophysics and Environmental Engineering, having authored 27 papers that have together received 3.4k indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (10 papers), Multimodal Machine Learning Applications (5 papers), Sentiment Analysis and Opinion Mining (2 papers), CO2 Sequestration and Geologic Interactions (2 papers), Hate Speech and Cyberbullying Detection (2 papers), Nonlinear Waves and Solitons (2 papers) and Geophysical and Geoelectrical Methods (2 papers). The work is most often cited by research in Artificial Intelligence (2.9k citations), Computer Vision and Pattern Recognition (860 citations), Health Informatics (47 citations), Computational Mathematics (9 citations) and General Social Sciences (48 citations). Samuel Bowman has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Amanpreet Singh, Felix Hill, Julian Michael, Omer Levy, Alex Wang, Alexis Conneau, Guillaume Lample, Ruty Rinott, Adina Williams and Veselin Stoyanov. Their work appears in journals such as Aquatic Geochemistry, International Journal of RF and Microwave Computer-Aided Engineering, Nature Communications, Language Resources and Evaluation and Geothermics.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026