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.
Micrometre-scale silicon electro-optic modulator
20051.8k citationsQianfan Xu, Bradley S. Schmidt et al.Natureprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Sameer Pradhan
Since
Specialization
Citations
This map shows the geographic impact of Sameer Pradhan'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 Sameer Pradhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sameer Pradhan more than expected).
This network shows the impact of papers produced by Sameer Pradhan. 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 Sameer Pradhan. The network helps show where Sameer Pradhan may publish in the future.
Co-authorship network of co-authors of Sameer Pradhan
This figure shows the co-authorship network connecting the top 25 collaborators of Sameer Pradhan.
A scholar is included among the top collaborators of Sameer Pradhan 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 Sameer Pradhan. Sameer Pradhan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
O’Gorman, Tim, et al.. (2018). The New Propbank: Aligning Propbank with AMR through POS Unification. Language Resources and Evaluation.6 indexed citations
Pradhan, Sameer & Marianna Apidianaki. (2016). Proceedings of ACL-2016 System Demonstrations.. Meeting of the Association for Computational Linguistics.1 indexed citations
Miller, Timothy A., Steven Bethard, Dmitriy Dligach, et al.. (2013). Discovering Temporal Narrative Containers in Clinical Text. Meeting of the Association for Computational Linguistics. 18–26.11 indexed citations
10.
Pradhan, Sameer, Alessandro Moschitti, Nianwen Xue, Olga Uryupina, & Yuchen Zhang. (2012). CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes. Institutional Research Information System (Università degli Studi di Trento). 1–40.376 indexed citations
11.
Pradhan, Sameer, Alessandro Moschitti, & Nianwen Xue. (2012). Joint Conference on EMNLP and CoNLL - Shared Task. Empirical Methods in Natural Language Processing.32 indexed citations
Hacıoğlu, Kadri, Sameer Pradhan, Wayne Ward, James Martin, & Daniel Jurafsky. (2004). Semantic Role Labeling by Tagging Syntactic Chunks. 110–113.63 indexed citations
17.
Pradhan, Sameer, Wayne Ward, Kadri Hacıoğlu, James Martin, & Daniel Jurafsky. (2004). Shallow Semantic Parsing using Support Vector Machines.. North American Chapter of the Association for Computational Linguistics. 233–240.264 indexed citations
Nielsen, Rodney D. & Sameer Pradhan. (2004). Mixing Weak Learners in Semantic Parsin. Empirical Methods in Natural Language Processing. 98(7). 80–87.13 indexed citations
20.
Pradhan, Sameer, Steven Bethard, Wayne Ward, et al.. (2002). Building a Foundation System for Producing Short Answers to Factual Questions.. Text REtrieval Conference.6 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.