Aishwarya Agrawal

6.7k total citations · 2 hit papers
21 papers, 2.9k citations indexed

About

Aishwarya Agrawal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Aishwarya Agrawal has authored 21 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 2 papers in Experimental and Cognitive Psychology. Recurrent topics in Aishwarya Agrawal's work include Multimodal Machine Learning Applications (12 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Aishwarya Agrawal is often cited by papers focused on Multimodal Machine Learning Applications (12 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Aishwarya Agrawal collaborates with scholars based in Canada, United States and United Kingdom. Aishwarya Agrawal's co-authors include Dhruv Batra, Devi Parikh, Margaret Mitchell, C. Lawrence Zitnick, Stanislaw Antol, Jiasen Lu, Nasrin Mostafazadeh, Ishan Misra, Ting-Hao Huang and Ross Girshick and has published in prestigious journals such as International Journal of Computer Vision, Computer Vision and Image Understanding and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Aishwarya Agrawal

17 papers receiving 2.8k citations

Hit Papers

VQA: Visual Question Answering 2015 2026 2018 2022 2015 2016 500 1000 1.5k 2.0k
What are hit papers?

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.

  1. VQA: Visual Question Answering
    2015 2.3k citations Stanislaw Antol, Aishwarya Agrawal et al. profile →
  2. VQA: Visual Question Answering
    2016 345 citations Aishwarya Agrawal, Jiasen Lu et al. International Journal of Computer Vision profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aishwarya Agrawal Canada 8 2.5k 2.0k 77 76 65 21 2.9k
Stanislaw Antol United States 4 2.3k 0.9× 1.9k 0.9× 72 0.9× 73 1.0× 62 1.0× 5 2.7k
Jiasen Lu United States 13 4.2k 1.7× 3.2k 1.6× 88 1.1× 109 1.4× 101 1.6× 17 4.8k
Damien Teney Australia 13 3.4k 1.4× 2.3k 1.2× 35 0.5× 37 0.5× 47 0.7× 29 3.8k
Justin Johnson United States 5 2.7k 1.1× 1.9k 0.9× 27 0.4× 38 0.5× 33 0.5× 7 3.0k
Oliver Groth United Kingdom 3 2.7k 1.1× 1.9k 0.9× 28 0.4× 38 0.5× 30 0.5× 8 3.0k
Julia Hockenmaier United States 21 3.2k 1.3× 3.4k 1.7× 31 0.4× 156 2.1× 90 1.4× 69 5.0k
Rico Sennrich Switzerland 27 944 0.4× 2.7k 1.3× 33 0.4× 224 2.9× 97 1.5× 109 3.1k
Radu Soricut United States 17 1.2k 0.5× 2.0k 1.0× 32 0.4× 187 2.5× 43 0.7× 42 2.5k
Jinsong Su China 26 886 0.4× 1.7k 0.8× 20 0.3× 145 1.9× 71 1.1× 153 2.2k
Weiping Wang China 24 1.1k 0.4× 846 0.4× 29 0.4× 129 1.7× 91 1.4× 142 1.8k

Countries citing papers authored by Aishwarya Agrawal

Since Specialization
Citations

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

Fields of papers citing papers by Aishwarya Agrawal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aishwarya Agrawal

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

All Works

20 of 20 papers shown
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2.
Zhang, Le, Qian Yang, & Aishwarya Agrawal. (2025). Assessing and Learning Alignment of Unimodal Vision and Language Models. 14604–14614. 1 indexed citations
3.
Gavves, Efstratios, et al.. (2025). CTRL-O: Language-Controllable Object-Centric Visual Representation Learning. 29523–29533.
4.
Mañas, Oscar, et al.. (2024). Improving Automatic VQA Evaluation Using Large Language Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 4171–4179. 9 indexed citations
5.
Jain, Kanishk, et al.. (2024). Benchmarking Vision Language Models for Cultural Understanding. 5769–5790. 8 indexed citations
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Agrawal, Aishwarya, et al.. (2024). VisMin: Visual Minimal-Change Understanding. 107795–107829. 1 indexed citations
9.
Bugliarello, Emanuele, et al.. (2023). Measuring Progress in Fine-grained Vision-and-Language Understanding. 1559–1582. 4 indexed citations
10.
11.
Zhang, Le, et al.. (2023). MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Model. 1195–1210. 3 indexed citations
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13.
Agrawal, Aishwarya, Damien Teney, & Aida Nematzadeh. (2022). Vision-Language Pretraining: Current Trends and the Future. 38–43. 4 indexed citations
14.
Agrawal, Aishwarya, et al.. (2017). Resolving vision and language ambiguities together: Joint segmentation & prepositional attachment resolution in captioned scenes. Computer Vision and Image Understanding. 163. 101–112. 9 indexed citations
15.
Huang, Ting-Hao, Francis Ferraro, Nasrin Mostafazadeh, et al.. (2016). Visual Storytelling. 1233–1239. 138 indexed citations
16.
Agrawal, Aishwarya, Jiasen Lu, Stanislaw Antol, et al.. (2016). VQA: Visual Question Answering. International Journal of Computer Vision. 123(1). 4–31. 345 indexed citations breakdown →
17.
Antol, Stanislaw, Aishwarya Agrawal, Jiasen Lu, et al.. (2015). VQA: Visual Question Answering. 2425–2433. 2331 indexed citations breakdown →
18.
Agrawal, Aishwarya & Shanmuganathan Raman. (2014). A novel LBP based operator for tone mapping HDR images. 21. 1–6. 1 indexed citations
19.
Agrawal, Aishwarya, et al.. (2014). Optically clearing tissue as an initial step for 3D imaging of core biopsies to diagnose pancreatic cancer. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8941. 89410N–89410N. 3 indexed citations
20.
Sarkar, Ashutosh, et al.. (2012). Single or Multiple Sourcing: A Method for Determining the Optimal Size of the Supply Base. 3(1-2). 17–31. 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.

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