Vihan Jain

4.6k total citations · 1 hit paper
12 papers, 2.2k citations indexed

About

Vihan Jain is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research. According to data from OpenAlex, Vihan Jain has authored 12 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 3 papers in Management Science and Operations Research. Recurrent topics in Vihan Jain's work include Topic Modeling (5 papers), Multimodal Machine Learning Applications (5 papers) and Speech and dialogue systems (3 papers). Vihan Jain is often cited by papers focused on Topic Modeling (5 papers), Multimodal Machine Learning Applications (5 papers) and Speech and dialogue systems (3 papers). Vihan Jain collaborates with scholars based in United States. Vihan Jain's co-authors include Heng-Tze Cheng, Tushar Chandra, Xiaobing Liu, Glen Anderson, Wei Koong Chai, Jeremiah Harmsen, Greg S. Corrado, Rohan Anil, Lichan Hong and Levent Koç and has published in prestigious journals such as Microelectronics Reliability, arXiv (Cornell University) and Reliability Engineering.

In The Last Decade

Vihan Jain

12 papers receiving 2.1k 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.

Wide & Deep Learning for Recommender Systems

2016 2.0k citations Heng-Tze Cheng, Levent Koç et al. profile →

Peers

Vihan Jain

IS

AI

CVPR

MSOR

CNC

Rohan Anil United States

Hemal Shah United States

Jeremiah Harmsen United States

Heng-Tze Cheng United States

Weike Pan China

Levent Koç Türkiye

Ruiming Tang China

Peng Jiang China

Chen Gao China

Shoujin Wang China

Rohan Anil United States

Vihan Jain

1.5k ×1.0

IS

1.2k ×0.9

AI

680 ×0.9

CVPR

281 ×0.8

MSOR

273 ×1.0

CNC

Citations per year, relative to Vihan Jain Vihan Jain (= 1×) peers Rohan Anil

Countries citing papers authored by Vihan Jain

Since Specialization

Citations

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

Fields of papers citing papers by Vihan Jain

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vihan Jain

This figure shows the co-authorship network connecting the top 25 collaborators of Vihan Jain. A scholar is included among the top collaborators of Vihan Jain 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 Vihan Jain. Vihan Jain 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:

12 of 12 papers shown

1.

Zhao, Ming, Peter Anderson, Vihan Jain, et al.. (2021). On the Evaluation of Vision-and-Language Navigation Instructions. 1302–1316. 25 indexed citations

2.

Zhang, Bowen, Hexiang Hu, Vihan Jain, Eugene Ie, & Fei Sha. (2020). Learning to Represent Image and Text with Denotation Graph. 823–839. 14 indexed citations

3.

Mladenov, Martin, Chih‐Wei Hsu, Vihan Jain, et al.. (2020). Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG. 591–593. 16 indexed citations

4.

Jain, Vihan, et al.. (2019). Effective and General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping. arXiv (Cornell University). 12 indexed citations

5.

Wang, Xin, et al.. (2019). Natural Language Grounded Multitask Navigation. 3 indexed citations

6.

Ilharco, Gabriel, Vihan Jain, Alexander Ku, Eugene Ie, & Jason Baldridge. (2019). General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping. arXiv (Cornell University). 19 indexed citations

7.

Jain, Vihan, et al.. (2019). Multi-modal Discriminative Model for Vision-and-Language Navigation. 15 indexed citations

8.

Jain, Vihan, et al.. (2019). Transferable Representation Learning in Vision-and-Language Navigation. 7403–7412. 49 indexed citations

9.

Ie, Eugene, Vihan Jain, Jing Wang, et al.. (2019). SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets. 2592–2599. 66 indexed citations

10.

Cheng, Heng-Tze, Levent Koç, Jeremiah Harmsen, et al.. (2016). Wide & Deep Learning for Recommender Systems. 7–10. 1997 indexed citations breakdown →

11.

Jain, Vihan & Krishna Gopal. (1986). An algorithm for determining the best path in a computer communication network. Reliability Engineering. 15(4). 299–305. 1 indexed citations

12.

Jain, Vihan & Krishna Gopal. (1986). An algorithm for determining the most reliable path of a network. Microelectronics Reliability. 26(5). 883–884. 3 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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