Adam Pauls

919 total citations
24 papers, 558 citations indexed

About

Adam Pauls is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Adam Pauls has authored 24 papers receiving a total of 558 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Adam Pauls's work include Topic Modeling (19 papers), Natural Language Processing Techniques (19 papers) and Speech and dialogue systems (6 papers). Adam Pauls is often cited by papers focused on Topic Modeling (19 papers), Natural Language Processing Techniques (19 papers) and Speech and dialogue systems (6 papers). Adam Pauls collaborates with scholars based in United States, Canada and Germany. Adam Pauls's co-authors include Dan Klein, Giuseppe Carenini, Brett Gladman, Emmanouil Antonios Platanios, John DeNero, Raymond T. Ng, Sam Thomson, Greg Durrett, Benjamin Van Durme and Subhro Roy and has published in prestigious journals such as Meteoritics and Planetary Science, Computational Intelligence and Empirical Methods in Natural Language Processing.

In The Last Decade

Adam Pauls

24 papers receiving 503 citations

Peers

Adam Pauls
Comparison fields: 5 of 42
  • Artificial Intelligence 482
  • Computer Vision and Pattern Recognition 83
  • Information Systems 67
  • Astronomy and Astrophysics 42
  • Molecular Biology 18
Replace R. B. Mishra with:
R. B. Mishra India
Bill Hibbard United States
Michael F. Ringenburg United States
Pablo Loyola Japan
Mikhail Khodak United States
Yueyang Zhang China
Xu Chun China
John Waldron Ireland
Wahid Bhimji United States
R. B. Mishra India View profile →
Citations per field, relative to Adam Pauls
Adam Pauls · 1×
Citations per year, relative to Adam Pauls
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Countries citing papers authored by Adam Pauls

Since Specialization
Citations

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

Fields of papers citing papers by Adam Pauls

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Pauls

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Pauls. A scholar is included among the top collaborators of Adam Pauls 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 Adam Pauls. Adam Pauls 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
# Work Indexed citations
1 1
2 2
3 1
4 7
5 87
6 8
7 24
8
Large-Scale Syntactic Language Modeling with Treelets
32
9
Syntactic Transfer Using a Bilingual Lexicon
37
10 52
11
Faster and Smaller N-Gram Language Models
93
12
Top-Down K-Best A* Parsing
5
13
Unsupervised Syntactic Alignment with Inversion Transduction Grammars
12
14
Hierarchical A* Parsing with Bridge Outside Scores
1
15
Efficient Optimization of an MDL-Inspired Objective Function for Unsupervised Part-Of-Speech Tagging
8
16
Bayesian Inference for Finite-State Transducers
15
17 21
18 19
19 15
20
Learning Structured Models for Phone Recognition
11

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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