Sam Thomson

1.6k citations
20 papers · 714 · h-index 10

Impact in

Papers in

    • Natural Language Processing Techniques 16
    • Topic Modeling 15
    • Speech and dialogue systems 4
    • Speech Recognition and Synthesis 2
    • Machine Learning and Algorithms 2
    • Text Readability and Simplification 1
    • Advanced Graph Neural Networks 1
    • Multimodal Machine Learning Applications 4

Sam Thomson

19 papers receiving 640 citations

Peers

Sam Thomson
Comparison fields: 5 of 68
  • Artificial Intelligence 647
  • Computer Vision and Pattern Recognition 112
  • Health Informatics 3
  • Information Systems 52
  • Computational Mathematics 1
Replace Điền Đinh with:
Điền Đinh Vietnam
Mohamed Yahya Germany
Dingfan Chen Germany
Ehsan Shareghi Australia
Ben Bogin United States
Vishrav Chaudhary United States
Cem Akkaya United States
Shijie Wu United States
Cheol-Young Ock South Korea
Iñigo López-Gazpio Spain
Sam Thomson relative to Điền Đinh Vietnam Điền Đinh's profile →
Citations per field
00.5×4.7×
Điền Đinh · 1×
Citations per year

Countries citing papers authored by Sam Thomson

Since Specialization
Citations

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

Fields of papers citing papers by Sam Thomson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sam Thomson, 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 Sam Thomson Line = papers co-authored together Sam Thomson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2014202
2 2015168
3 202195
4 201844
5 201842
6 201537
7 200033
8 202125
9 201813
10 201810
11 20219
12
Research and Development Report
20159
13 20148
14 20188
15 20223
16 20223
17 20232
18 20222
19 20061
20 20220

About Sam Thomson

Sam Thomson is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Ecology, Evolution, Behavior and Systematics and Management, Monitoring, Policy and Law, having authored 20 papers that have together received 714 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (16 papers), Topic Modeling (15 papers), Multimodal Machine Learning Applications (4 papers), Speech and dialogue systems (4 papers), Speech Recognition and Synthesis (2 papers), Machine Learning and Algorithms (2 papers), Text Readability and Simplification (1 paper) and Advanced Graph Neural Networks (1 paper). The work is most often cited by research in Artificial Intelligence (647 citations), Computer Vision and Pattern Recognition (112 citations), Health Informatics (3 citations), Information Systems (52 citations) and Computational Mathematics (1 citation). Sam Thomson has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Noah A. Smith, Jeffrey Flanigan, Chris Dyer, Jaime Carbonell, Fei Liu, Norman Sadeh, Swabha Swayamdipta, Emmanouil Antonios Platanios, Adam Pauls and Hao Peng. Their work appears in journals such as Frontiers in Genetics, Archives of Pathology & Laboratory Medicine, Qualitative Inquiry, Edinburgh Research Explorer and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

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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