Kshitij Bansal
- Artificial Intelligence
- Computational Theory and Mathematics
- Information Systems
- Software
- General Dentistry
- Co-authors
- Christian SzegedyMarkus N. RabeSarah M. LoosDennis LeeAshima ValiathanCesare TinelliNidhi BansalClark Barrett
- Topics
- Topic Modeling (3 papers)Natural Language Processing Techniques (3 papers)Logic, Reasoning, and Knowledge (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Automated ReasoningarXiv (Cornell University)
- Partner nations
- United StatesIndia
In The Last Decade
Kshitij Bansal
7 papers receiving 33 citations
Peers
Comparison fields: 5 of 16
- Artificial Intelligence 32
- Computational Theory and Mathematics 10
- Information Systems 9
- Software 4
- General Dentistry 3
Countries citing papers authored by Kshitij Bansal
This map shows the geographic impact of Kshitij Bansal'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 Kshitij Bansal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kshitij Bansal more than expected).
Fields of papers citing papers by Kshitij Bansal
This network shows the impact of papers produced by Kshitij Bansal. 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 Kshitij Bansal. The network helps show where Kshitij Bansal may publish in the future.
Co-authorship network of co-authors of Kshitij Bansal
This figure shows the co-authorship network connecting the top 25 collaborators of Kshitij Bansal. A scholar is included among the top collaborators of Kshitij Bansal 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 Kshitij Bansal. Kshitij Bansal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Mathematical Reasoning via Self-supervised Skip-tree Training | 3 |
| 3 | Language Modeling for Formal Mathematics | 1 |
| 4 | Mathematical Reasoning in Latent Space | 4 |
| 5 | 1 | |
| 6 | HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving | 21 |
| 7 | HOList: An Environment for Machine Learning of Higher-Order Theorem Proving (extended version) | 2 |
| 8 | 3 | |
| 9 | 3 |
About Kshitij Bansal
Kshitij Bansal is a scholar working on Theoretical Computer Science, Hardware and Architecture and Internal Medicine, having authored 9 papers that have together received 38 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (3 papers) and Logic, Reasoning, and Knowledge (2 papers). The work is most often cited by research in General Dentistry (3 citations), Software (4 citations) and Artificial Intelligence (32 citations). Kshitij Bansal has collaborated with scholars based in United States and India. Frequent co-authors include Christian Szegedy, Markus N. Rabe, Sarah M. Loos, Dennis Lee, Ashima Valiathan, Cesare Tinelli, Nidhi Bansal, Clark Barrett, Andrew Reynolds and Omer Tripp. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Automated Reasoning and arXiv (Cornell University).
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.