Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
This map shows the geographic impact of Mark Johnson'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 Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Johnson more than expected).
This network shows the impact of papers produced by Mark Johnson. 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 Johnson. The network helps show where Mark Johnson may publish in the future.
Co-authorship network of co-authors of Mark Johnson
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Johnson.
A scholar is included among the top collaborators of Mark Johnson 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 Johnson. Mark Johnson 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
1.
Johnson, Mark. (2017). Improving Cohesion in L2 Writing: A Three-Strand Approach to Building Lexical Cohesion.. English Teaching Forum. 55(4). 2–13.4 indexed citations
2.
Honnibal, Matthew & Mark Johnson. (2015). An Improved Non-monotonic Transition System for Dependency Parsing. 1373–1378.340 indexed citations breakdown →
3.
Zhao, Zhendong, Lan Du, Benjamin Börschinger, et al.. (2015). Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing.193 indexed citations
4.
Honnibal, Matthew, Yoav Goldberg, & Mark Johnson. (2013). A Non-Monotonic Arc-Eager Transition System for Dependency Parsing. 163–172.24 indexed citations
5.
Johnson, Mark, Katherine Demuth, & Michael C. Frank. (2012). Exploiting Social Information in Grounded Language Learning via Grammatical Reduction. Meeting of the Association for Computational Linguistics. 883–891.8 indexed citations
6.
Börschinger, Benjamin, Bevan Jones, & Mark Johnson. (2011). Reducing Grounded Learning Tasks To Grammatical Inference. Empirical Methods in Natural Language Processing. 1416–1425.26 indexed citations
7.
Johnson, Mark, et al.. (2011). Using Language Models and Latent Semantic Analysis to Characterise the N400m Neural Response. Clinical EEG and Neuroscience. 43(3). 38–46.9 indexed citations
Naseem, Tahira, Harr Chen, Regina Barzilay, & Mark Johnson. (2010). Using Universal Linguistic Knowledge to Guide Grammar Induction. DSpace@MIT (Massachusetts Institute of Technology). 1234–1244.83 indexed citations
11.
Johnson, Mark, et al.. (2010). Reranking the Berkeley and Brown Parsers. North American Chapter of the Association for Computational Linguistics. 665–668.14 indexed citations
12.
Johnson, Mark, Katherine Demuth, Bevan Jones, & Michael J. Black. (2010). Synergies in learning words and their referents. Neural Information Processing Systems. 23. 1018–1026.18 indexed citations
13.
McClosky, David, Eugene Charniak, & Mark Johnson. (2010). Automatic Domain Adaptation for Parsing. North American Chapter of the Association for Computational Linguistics. 28–36.92 indexed citations
14.
Johnson, Mark & Katherine Demuth. (2010). Unsupervised phonemic Chinese word segmentation using Adaptor Grammars. International Conference on Computational Linguistics. 528–536.10 indexed citations
15.
Goldwater, Sharon & Mark Johnson. (2004). Proceedings of the Seventh Meeting of the ACL Special Interest Group in Computational Phonology.2 indexed citations
16.
Altün, Yasemin, Thomas Hofmann, & Mark Johnson. (2002). Discriminative Learning for Label Sequences via Boosting. MPG.PuRe (Max Planck Society). 15. 1001–1008.32 indexed citations
17.
Lakoff, George, et al.. (1999). Leven in metaforen.
18.
Hodgkinson, J., et al.. (1997). A Very Efficient Sampling Technique for Fibre-Remote Optical Emission Spectroscopy of Aqueous Solutions.. ePrints Soton (University of Southampton). 3107. 260–271.
19.
Johnson, Mark. (1989). The Computational Complexity of Tomita's Algorithm.. 203–208.6 indexed citations
20.
Lakoff, George, et al.. (1986). Metáforas de la vida cotidiana. Cátedra eBooks.153 indexed citations
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.