Chaitanya Malaviya
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Experimental and Cognitive Psychology
- Information Systems
- Molecular Biology
- Co-authors
- Yejin ChoiAntoine BosselutHannah RashkinMaarten SapAslı ÇelikyılmazMark YatskarDan RothChandra Bhagavatula
- Topics
- Natural Language Processing Techniques (8 papers)Topic Modeling (8 papers)Advanced Graph Neural Networks (3 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionExperimental and Cognitive Psychology
- Journals
- Transactions of the Association for Computational LinguisticsInfoscience (Ecole Polytechnique Fédérale de Lausanne)arXiv (Cornell University)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Chaitanya Malaviya
10 papers receiving 476 citations
Hit Papers
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 453
- Computer Vision and Pattern Recognition 118
- Experimental and Cognitive Psychology 43
- Information Systems 35
- Molecular Biology 28
Countries citing papers authored by Chaitanya Malaviya
This map shows the geographic impact of Chaitanya Malaviya'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 Chaitanya Malaviya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaitanya Malaviya more than expected).
Fields of papers citing papers by Chaitanya Malaviya
This network shows the impact of papers produced by Chaitanya Malaviya. 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 Chaitanya Malaviya. The network helps show where Chaitanya Malaviya may publish in the future.
Co-authorship network of co-authors of Chaitanya Malaviya
This figure shows the co-authorship network connecting the top 25 collaborators of Chaitanya Malaviya. A scholar is included among the top collaborators of Chaitanya Malaviya 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 Chaitanya Malaviya. Chaitanya Malaviya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 8 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | G-DAUG: Generative Data Augmentation for Commonsense Reasoning | 5 |
| 11 | COMET: Commonsense Transformers for Automatic Knowledge Graph Constructionbreakdown → | 464 |
| 12 | COMET: Commonsense Transformers for Knowledge Graph Construction | 8 |
| 13 | Exploiting Structural and Semantic Context for Commonsense Knowledge Base Completion | 5 |
About Chaitanya Malaviya
Chaitanya Malaviya is a scholar working on Artificial Intelligence, General Social Sciences and Computer Science Applications, having authored 13 papers that have together received 497 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Artificial Intelligence (453 citations), Computer Vision and Pattern Recognition (118 citations) and Experimental and Cognitive Psychology (43 citations). Chaitanya Malaviya has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Yejin Choi, Antoine Bosselut, Hannah Rashkin, Maarten Sap, Aslı Çelikyılmaz, Mark Yatskar, Dan Roth, Chandra Bhagavatula, Sihao Chen and Swabha Swayamdipta. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Infoscience (Ecole Polytechnique Fédérale de Lausanne) 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.