Stella Frank

20 papers receiving 372 citations

Peers

Stella Frank
Comparison fields: 5 of 46
  • Artificial Intelligence 331
  • Computer Vision and Pattern Recognition 251
  • Experimental and Cognitive Psychology 21
  • Language and Linguistics 17
  • Developmental and Educational Psychology 15
Replace Katharina Kann with:
Katharina Kann United States
Shijie Wu United States
Aida Nematzadeh Canada
Johannes Bjerva Denmark
R. Thomas McCoy United States
Sandro Pezzelle Netherlands
Denis Paperno Italy
Allyson Ettinger United States
Jon Gauthier United States
Alex Warstadt United States
Stella Frank relative to Katharina Kann United States Katharina Kann's profile →
Citations per field
00.5×
Katharina Kann · 1×
Citations per year

Countries citing papers authored by Stella Frank

Since Specialization
Citations

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

Fields of papers citing papers by Stella Frank

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stella Frank

This figure shows the co-authorship network connecting the top 25 collaborators of Stella Frank. A scholar is included among the top collaborators of Stella Frank 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 Stella Frank. Stella Frank is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 52
3 25
4 36
5
Simple kinship systems are more learnable.
0
6
Learner dynamics in a model of wug inflection: integrating frequency and phonology.
1
7 7
8 11
9 74
10 3
11
Proceedings of the First Conference on Machine Translation, WMT 2016, colocated with ACL 2016, August 11-12, Berlin, Germany
3
12 24
13 121
14
Proceedings of the 5th Workshop on Vision and Language, hosted by the 54th Annual Meeting of the Association for Computational Linguistics, VL@ACL 2016, August 12, Berlin, Germany
3
15 1
16
Splitting Compounds by Semantic Analogy
8
17 3
18 4
19
Evaluating Models of Syntactic Category Acquisition without Using a Gold Standard
6
20 1

About Stella Frank

Stella Frank is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Developmental and Educational Psychology, having authored 21 papers that have together received 400 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Natural Language Processing Techniques (9 papers) and Topic Modeling (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (251 citations), Artificial Intelligence (331 citations) and Health Informatics (5 citations). Stella Frank has collaborated with scholars based in United Kingdom, Denmark and United States. Frequent co-authors include Desmond Elliott, Lucia Specia, Khalil Sima’an, Emanuele Bugliarello, Fethi Bougares, Loïc Barrault, Daniel Hershcovich, Anders Søgaard, Iacer Calixto and Sharon Goldwater. Their work appears in journals such as Cognitive Science, Topics in Cognitive Science and Natural Language Engineering.

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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