Mark Steedman

19.1k total citations · 3 hit papers
209 papers, 9.3k citations indexed

About

Mark Steedman is a scholar working on Artificial Intelligence, Language and Linguistics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mark Steedman has authored 209 papers receiving a total of 9.3k indexed citations (citations by other indexed papers that have themselves been cited), including 155 papers in Artificial Intelligence, 41 papers in Language and Linguistics and 19 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mark Steedman's work include Natural Language Processing Techniques (123 papers), Topic Modeling (83 papers) and Speech and dialogue systems (45 papers). Mark Steedman is often cited by papers focused on Natural Language Processing Techniques (123 papers), Topic Modeling (83 papers) and Speech and dialogue systems (45 papers). Mark Steedman collaborates with scholars based in United Kingdom, United States and Australia. Mark Steedman's co-authors include Gerry T. M. Altmann, Julia Hockenmaier, Mark Johnson, Bharat Ram Ambati, Tejaswini Deoskar, Sharon Goldwater, Norman I. Badler, Catherine Pélachaud, Mike Lewis and Stephen Clark and has published in prestigious journals such as PLANT PHYSIOLOGY, Cognition and Language.

In The Last Decade

Mark Steedman

197 papers receiving 8.0k citations

Hit Papers

The Syntactic Process 1988 2026 2000 2013 2000 2015 1988 250 500 750

Peers

Mark Steedman
Comparison fields: 5 of 164
  • Artificial Intelligence 6.4k
  • Language and Linguistics 1.8k
  • Cognitive Neuroscience 1.3k
  • Computer Vision and Pattern Recognition 1.2k
  • Experimental and Cognitive Psychology 1.2k
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Citations per field, relative to Mark Steedman
Mark Steedman · 1×
Citations per year, relative to Mark Steedman
Mark Steedman · 1×

Countries citing papers authored by Mark Steedman

Since Specialization
Citations

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

Fields of papers citing papers by Mark Steedman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Steedman

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Steedman. A scholar is included among the top collaborators of Mark Steedman 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 Mark Steedman. Mark Steedman 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 9
3 16
4 6
5 4
6
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, 27-31 July 2011, John McIntyre Conference Centre, Edinburgh, UK, A meeting of SIGDAT, a Special Interest Group of the ACL
19
7
A Bayesian Mixture Model for PoS Induction Using Multiple Features
8
8
Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification
165
9
Two Decades of Unsupervised POS tagging---How Far Have We Come?
1
10
Unbounded Dependency Recovery for Parser Evaluation
52
11 6
12
Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky
8
13
An Annotation Scheme for Information Status in Dialogue.
57
14
Object-Extraction and Question-Parsing using CCG.
29
15
Where Does Compositionality Come From
0
16
Acquiring Compact Lexicalized Grammars from a Cleaner Treebank.
63
17 6
18
Dynamic semantics for tense and aspect
6
19 138
20 182

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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