Patrick Schramowski

2.8k citations
32 papers · 940 · 1 hit paper · h-index 14

Impact in

    • Ethics and Social Impacts of AI
    • Explainable Artificial Intelligence (XAI)
    • Adversarial Robustness in Machine Learning
    • Topic Modeling
    • Domain Adaptation and Few-Shot Learning

Papers in

Patrick Schramowski

29 papers receiving 916 citations

Patrick Schramowski's Hit Papers

Large pre-trained language models contain human-like biases of what is right and wrong to do 2022 · 203 citations
2030+1+2Years since publication50100150200

Peers

Patrick Schramowski
Comparison fields: 5 of 96
  • Safety Research 192
  • Artificial Intelligence 422
  • Health Informatics 25
  • Computer Vision and Pattern Recognition 239
  • Analytical Chemistry 28
Replace Joyce Nakatumba Nabende with:
Joyce Nakatumba Nabende Uganda
Yuxin Huang China
Reid Pryzant United States
Shauli Ravfogel Israel
Stefano Teso Italy
Maxwell Forbes United States
Sara Hooker United States
Wenliang Dai Hong Kong
Haixing Dai United States
Anton Bakhtin United States
Patrick Schramowski relative to Joyce Nakatumba Nabende Uganda Joyce Nakatumba Nabende's profile →
Citations per field
00.5×2×4×6×8.5×
Joyce Nakatumba Nabende · 1×
Citations per year

Countries citing papers authored by Patrick Schramowski

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Schramowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Large pre-trained language models contain human-like biases of what is right and wrong to do
Hit paper breakdown →
2022203
2 2020151
3 2023117
4 202253
5 202146
6 202239
7 202439
8 201936
9 201933
10 202429
11 202327
12 202122
13 202021
14 202319
15 202114
16 202314
17 202212
18 202310
19 202310
20 202310

About Patrick Schramowski

Patrick Schramowski is a scholar working on Artificial Intelligence, Safety Research, Computer Vision and Pattern Recognition, Analytical Chemistry and Structural Biology, having authored 32 papers that have together received 940 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Ethics and Social Impacts of AI (9 papers), Explainable Artificial Intelligence (XAI) (8 papers), Generative Adversarial Networks and Image Synthesis (7 papers), Natural Language Processing Techniques (5 papers), Multimodal Machine Learning Applications (3 papers), Advanced Neural Network Applications (3 papers) and Psychology of Moral and Emotional Judgment (2 papers). The work is most often cited by research in Safety Research (192 citations), Artificial Intelligence (422 citations), Health Informatics (25 citations), Computer Vision and Pattern Recognition (239 citations) and Analytical Chemistry (28 citations). Patrick Schramowski has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Kristian Kersting, Constantin A. Rothkopf, Manuel Brack, Cigdem Turan, Wolfgang Stammer, Anna Brugger, Anne‐Katrin Mahlein, Stefano Teso, Lukas Struppek and Dominik Hintersdorf. Their work appears in journals such as Nature Machine Intelligence, Journal of Artificial Intelligence Research, Business & Information Systems Engineering, Plant Pathology and Remote Sensing.

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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