Armen Aghajanyan

1.3k total citations · 1 hit paper
7 papers, 427 citations indexed

About

Armen Aghajanyan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Armen Aghajanyan has authored 7 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 1 paper in Molecular Biology. Recurrent topics in Armen Aghajanyan's work include Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers) and Multimodal Machine Learning Applications (4 papers). Armen Aghajanyan is often cited by papers focused on Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers) and Multimodal Machine Learning Applications (4 papers). Armen Aghajanyan collaborates with scholars based in United States, Canada and Armenia. Armen Aghajanyan's co-authors include Luke Zettlemoyer, Gargi Ghosh, Dmytro Okhonko, Christoph Feichtenhofer, Po-Yao Huang, Hu Xu, Florian Metze, Xilun Chen, Sonal Gupta and Anchit Gupta and has published in prestigious journals such as Journal of Chemical Information and Modeling, arXiv (Cornell University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Armen Aghajanyan

7 papers receiving 408 citations

Hit Papers

align trajectories

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.

VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

2021 247 citations Hu Xu, Gargi Ghosh et al. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Armen Aghajanyan United States	6	290	253	24	15	11	7	427
А.В. Куракин United States	6	284 1.0×	151 0.6×	14 0.6×	21 1.4×	13 1.2×	8	361
Ajinkya Kale United States	7	140 0.5×	165 0.7×	50 2.1×	10 0.7×	9 0.8×	15	274
Yuejian Fang China	6	413 1.4×	431 1.7×	26 1.1×	16 1.1×	6 0.5×	23	548
Saksham Singhal China	7	368 1.3×	289 1.1×	20 0.8×	25 1.7×	6 0.5×	10	507
Shangling Jui China	8	348 1.2×	282 1.1×	13 0.5×	29 1.9×	8 0.7×	23	467
Vedanuj Goswami United States	7	410 1.4×	421 1.7×	15 0.6×	27 1.8×	6 0.5×	13	581
Junliang Guo China	12	292 1.0×	175 0.7×	20 0.8×	16 1.1×	9 0.8×	37	448
Zhen Qin United States	9	158 0.5×	209 0.8×	33 1.4×	18 1.2×	20 1.8×	24	301
Vincent Perot United States	3	260 0.9×	186 0.7×	11 0.5×	13 0.9×	7 0.6×	3	335
Curtis Wigington United States	9	191 0.7×	217 0.9×	11 0.5×	22 1.5×	4 0.4×	17	339

Countries citing papers authored by Armen Aghajanyan

Since Specialization

Citations

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

Fields of papers citing papers by Armen Aghajanyan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Armen Aghajanyan

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Hambardzumyan, Karen, et al.. (2024). BartSmiles: Generative Masked Language Models for Molecular Representations. Journal of Chemical Information and Modeling. 64(15). 5832–5843. 7 indexed citations

2.

Sachan, Devendra Singh, Michael Lewis, Mandar Joshi, et al.. (2022). Improving Passage Retrieval with Zero-Shot Question Generation. 3781–3797. 37 indexed citations

3.

Aghajanyan, Armen, Barlas Oğuz, Dmytro Okhonko, et al.. (2022). CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training. 8 indexed citations

4.

Aghajanyan, Armen, et al.. (2021). Muppet: Massive Multi-task Representations with Pre-Finetuning. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 5799–5811. 104 indexed citations

5.

Xu, Hu, Gargi Ghosh, Po-Yao Huang, et al.. (2021). VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 6787–6800. 247 indexed citations breakdown →

6.

Lewis, Mike, Marjan Ghazvininejad, Gargi Ghosh, et al.. (2020). Pre-training via Paraphrasing. arXiv (Cornell University). 33. 18470–18481. 23 indexed citations

7.

Aghajanyan, Armen, Song Xia, & Saurabh Tiwary. (2019). Towards Language Agnostic Universal Representations. 4033–4041. 1 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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