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.
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
2023272 citationsIshika Singh, Valts Blukis et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Jesse Thomason
Since
Specialization
Citations
This map shows the geographic impact of Jesse Thomason'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 Jesse Thomason with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jesse Thomason more than expected).
This network shows the impact of papers produced by Jesse Thomason. 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 Jesse Thomason. The network helps show where Jesse Thomason may publish in the future.
Co-authorship network of co-authors of Jesse Thomason
This figure shows the co-authorship network connecting the top 25 collaborators of Jesse Thomason.
A scholar is included among the top collaborators of Jesse Thomason 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 Jesse Thomason. Jesse Thomason is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Burns, Collin, Jesse Thomason, & Wesley Tansey. (2019). Interpreting Black Box Models with Statistical Guarantees.. arXiv (Cornell University).2 indexed citations
15.
Thomason, Jesse, et al.. (2017). Improving Black-box Speech Recognition using Semantic Parsing. International Joint Conference on Natural Language Processing. 2. 122–127.9 indexed citations
16.
Thomason, Jesse, et al.. (2017). Opportunistic Active Learning for Grounding Natural Language Descriptions. 67–76.16 indexed citations
17.
Thomason, Jesse, et al.. (2016). Learning multi-modal grounded linguistic semantics by playing I Spy. International Joint Conference on Artificial Intelligence. 3477–3483.39 indexed citations
18.
Thomason, Jesse, Shiqi Zhang, Raymond J. Mooney, & Peter Stone. (2015). Learning to interpret natural language commands through human-robot dialog. International Conference on Artificial Intelligence. 1923–1929.79 indexed citations
19.
Thomason, Jesse, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, & Raymond J. Mooney. (2014). Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild. International Conference on Computational Linguistics. 1218–1227.107 indexed citations
20.
Thomason, Jesse & Diane Litman. (2013). Differences in User Responses to a Wizard-of-Oz versus Automated System. North American Chapter of the Association for Computational Linguistics. 796–801.2 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.