Vikas Raunak

1.2k total citations
13 papers, 119 citations indexed

About

Vikas Raunak is a scholar working on Artificial Intelligence, Information Systems and Cellular and Molecular Neuroscience. According to data from OpenAlex, Vikas Raunak has authored 13 papers receiving a total of 119 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 2 papers in Information Systems and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Vikas Raunak's work include Natural Language Processing Techniques (11 papers), Topic Modeling (8 papers) and Text Readability and Simplification (2 papers). Vikas Raunak is often cited by papers focused on Natural Language Processing Techniques (11 papers), Topic Modeling (8 papers) and Text Readability and Simplification (2 papers). Vikas Raunak collaborates with scholars based in United States, India and United Kingdom. Vikas Raunak's co-authors include P. Geethanjali, Arul Menezes, Florian Metze, Matt Post, Shinji Watanabe, Siddharth Dalmia, Soumya Sen, V. K. Chaubey, Hany Hassan Awadalla and Amr Sharaf and has published in prestigious journals such as Optical Fiber Technology and Australasian Physical & Engineering Sciences in Medicine.

In The Last Decade

Vikas Raunak

10 papers receiving 115 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vikas Raunak United States	6	55	46	39	16	15	13	119
Novi Patricia Switzerland	4	59 1.1×	31 0.7×	24 0.6×	42 2.6×	16 1.1×	4	115
P. Ashok Babu India	6	26 0.5×	10 0.2×	29 0.7×	30 1.9×	7 0.5×	17	127
Pilhyeon Lee South Korea	7	119 2.2×	14 0.3×	21 0.5×	138 8.6×	9 0.6×	13	206
Ghassem Tofighi Canada	5	41 0.7×	22 0.5×	35 0.9×	37 2.3×	25 1.7×	6	159
Sigang Yu China	6	19 0.3×	8 0.2×	35 0.9×	8 0.5×	4 0.3×	12	79
Ankit Gupta Sweden	4	17 0.3×	6 0.1×	81 2.1×	9 0.6×	18 1.2×	7	135
Qaiser Mahmood Sweden	6	16 0.3×	16 0.3×	21 0.5×	56 3.5×	3 0.2×	10	94
Nikhil Garg France	9	100 1.8×	4 0.1×	37 0.9×	34 2.1×	6 0.4×	24	206
Martin Biehl Japan	5	23 0.4×	25 0.5×	84 2.2×	9 0.6×	4 0.3×	9	148

Countries citing papers authored by Vikas Raunak

Since Specialization

Citations

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

Fields of papers citing papers by Vikas Raunak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vikas Raunak

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

13 of 13 papers shown

1.

Dankers, Verna & Vikas Raunak. (2025). Memorization Inheritance in Sequence-Level Knowledge Distillation for Neural Machine Translation. 760–774.

2.

Raunak, Vikas, Tom Kocmi, & Matt Post. (2024). SLIDE: Reference-free Evaluation for Machine Translation using a Sliding Document Window. 205–211.

3.

Raunak, Vikas, Roman Grundkiewicz, & Marcin Junczys-Dowmunt. (2024). On Instruction-Finetuning Neural Machine Translation Models. 1155–1166.

4.

Raunak, Vikas, Arul Menezes, & Hany Hassan Awadalla. (2023). Dissecting In-Context Learning of Translations in GPT-3. 866–872. 2 indexed citations

5.

Raunak, Vikas, Amr Sharaf, Yiren Wang, Hany Hassan Awadalla, & Arul Menezes. (2023). Leveraging GPT-4 for Automatic Translation Post-Editing. 12009–12024. 12 indexed citations

6.

Raunak, Vikas, Arul Menezes, Matt Post, & Hany Hassan. (2023). Do GPTs Produce Less Literal Translations?. 1041–1050. 8 indexed citations

7.

Raunak, Vikas, Tom Kocmi, & Matt Post. (2023). Evaluating Metrics for Document-context Evaluation in Machine Translation. 812–814. 1 indexed citations

8.

Raunak, Vikas & Arul Menezes. (2022). Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks. 5153–5162. 4 indexed citations

9.

Raunak, Vikas, Matt Post, & Arul Menezes. (2022). SALTED: A Framework for SAlient Long-tail Translation Error Detection. 5163–5179. 6 indexed citations

10.

Dalmia, Siddharth, et al.. (2021). Searchable Hidden Intermediates for End-to-End Models of Decomposable Sequence Tasks. 1882–1896. 21 indexed citations

11.

Raunak, Vikas, Vaibhav Kumar, Vivek Gupta, & Florian Metze. (2020). On Dimensional Linguistic Properties of the Word Embedding Space. 156–165. 2 indexed citations

12.

Geethanjali, P. & Vikas Raunak. (2018). Identification of a feature selection based pattern recognition scheme for finger movement recognition from multichannel EMG signals. Australasian Physical & Engineering Sciences in Medicine. 41(2). 549–559. 54 indexed citations

13.

Sen, Soumya, Vikas Raunak, & V. K. Chaubey. (2005). Designing and simulation of a modified WDM ring network with improved grade of service. Optical Fiber Technology. 11(3). 266–277. 9 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.

Explore authors with similar magnitude of impact