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.
Automating string processing in spreadsheets using input-output examples
This map shows the geographic impact of Sumit Gulwani'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 Sumit Gulwani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumit Gulwani more than expected).
This network shows the impact of papers produced by Sumit Gulwani. 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 Sumit Gulwani. The network helps show where Sumit Gulwani may publish in the future.
Co-authorship network of co-authors of Sumit Gulwani
This figure shows the co-authorship network connecting the top 25 collaborators of Sumit Gulwani.
A scholar is included among the top collaborators of Sumit Gulwani 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 Sumit Gulwani. Sumit Gulwani is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Natarajan, Nagarajan, et al.. (2019). Learning Natural Programs from a Few Examples in Real-Time. International Conference on Artificial Intelligence and Statistics. 1714–1722.1 indexed citations
14.
Kalyan, Ashwin, et al.. (2018). Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples. International Conference on Learning Representations.8 indexed citations
15.
Jain, Prateek, et al.. (2017). FlashProfile: Interactive Synthesis of Syntactic Profiles.. eScholarship (California Digital Library).3 indexed citations
Gulwani, Sumit, et al.. (2015). FlashNormalize: programming by examples for text normalization. International Conference on Artificial Intelligence. 776–783.12 indexed citations
18.
Raza, Mohammad, Sumit Gulwani, & Nataša Milić-Frayling. (2015). Compositional program synthesis from natural language and examples. International Conference on Artificial Intelligence. 792–800.26 indexed citations
19.
Menon, Aditya Krishna, Omer Tamuz, Sumit Gulwani, Butler Lampson, & Adam Tauman Kalai. (2013). A Machine Learning Framework for Programming by Example. International Conference on Machine Learning. 28. 187–195.60 indexed citations
20.
Gulwani, Sumit, et al.. (2013). Automatically generating problems and solutions for natural deduction. International Joint Conference on Artificial Intelligence. 1968–1975.23 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.