Vikas Bhardwaj

404 total citations
10 papers, 190 citations indexed

About

Vikas Bhardwaj is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Epidemiology. According to data from OpenAlex, Vikas Bhardwaj has authored 10 papers receiving a total of 190 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Epidemiology. Recurrent topics in Vikas Bhardwaj's work include Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Speech and dialogue systems (2 papers). Vikas Bhardwaj is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Speech and dialogue systems (2 papers). Vikas Bhardwaj collaborates with scholars based in United States. Vikas Bhardwaj's co-authors include Yichao Lu, Rebecca J. Passonneau, Nancy Ide, Ansaf Salleb-Aouissi, Faisal Ladhak, Shaonan Zhang, Jason Sun, Hassan Malik, Sonal Gupta and Xintong Li and has published in prestigious journals such as Language Resources and Evaluation, arXiv (Cornell University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Vikas Bhardwaj

10 papers receiving 177 citations

Peers

Vikas Bhardwaj

AI

CVPR

MSOR

CSA

IS

Johnny Tian-Zheng Wei United States

Liunian Harold Li United States

Mihail Eric United States

Alex Marin United States

Tristan Thrush Israel

Gustavo Aguilar United States

Pablo Pedemonte United States

Xueliang Zhao China

Patrick Xia United States

Roberta Răileanu Israel

Johnny Tian-Zheng Wei United States

Vikas Bhardwaj

249 ×1.4

AI

49 ×1.1

CVPR

4 ×0.3

MSOR

15 ×1.3

CSA

26 ×3.7

IS

Citations per year, relative to Vikas Bhardwaj Vikas Bhardwaj (= 1×) peers Johnny Tian-Zheng Wei

Countries citing papers authored by Vikas Bhardwaj

Since Specialization

Citations

This map shows the geographic impact of Vikas Bhardwaj'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 Vikas Bhardwaj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikas Bhardwaj more than expected).

Fields of papers citing papers by Vikas Bhardwaj

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikas Bhardwaj. 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 Vikas Bhardwaj. The network helps show where Vikas Bhardwaj may publish in the future.

Co-authorship network of co-authors of Vikas Bhardwaj

This figure shows the co-authorship network connecting the top 25 collaborators of Vikas Bhardwaj. A scholar is included among the top collaborators of Vikas Bhardwaj 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 Vikas Bhardwaj. Vikas Bhardwaj is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Heidari, Peyman, Arash Einolghozati, Shashank Jain, et al.. (2021). Getting to Production with Few-shot Natural Language Generation Models. 66–76. 9 indexed citations

2.

Jain, Shashank, Peyman Heidari, Xintong Li, et al.. (2021). Building Adaptive Acceptability Classifiers for Neural NLG. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 682–697. 6 indexed citations

3.

Lu, Yichao, et al.. (2020). On the Evaluation of Contextual Embeddings for Zero-Shot Cross-Lingual Transfer Learning.. arXiv (Cornell University). 4 indexed citations

4.

Lu, Yichao, et al.. (2019). Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER. 1355–1360. 44 indexed citations

5.

Lu, Yichao, et al.. (2018). A neural interlingua for multilingual machine translation. 84–92. 50 indexed citations

6.

Passonneau, Rebecca J., Vikas Bhardwaj, Ansaf Salleb-Aouissi, & Nancy Ide. (2012). Multiplicity and word sense: evaluating and learning from multiply labeled word sense annotations. Language Resources and Evaluation. 46(2). 219–252. 23 indexed citations

7.

Malik, Hassan & Vikas Bhardwaj. (2011). Automatic Training Data Cleaning for Text Classification. 442–449. 7 indexed citations

8.

Malik, Hassan, et al.. (2011). Accurate information extraction for quantitative financial events. 2497–2500. 10 indexed citations

9.

Passonneau, Rebecca J., et al.. (2010). Word Sense Annotation of Polysemous Words by Multiple Annotators. Language Resources and Evaluation. 3244–3249. 19 indexed citations

10.

Bhardwaj, Vikas, Rebecca J. Passonneau, Ansaf Salleb-Aouissi, & Nancy Ide. (2010). Anveshan: A Framework for Analysis of Multiple Annotators' Labeling Behavior. 47–55. 18 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.

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