Kumar Shridhar

1.1k total citations
13 papers, 98 citations indexed

About

Kumar Shridhar is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kumar Shridhar has authored 13 papers receiving a total of 98 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kumar Shridhar's work include Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Intelligent Tutoring Systems and Adaptive Learning (2 papers). Kumar Shridhar is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Intelligent Tutoring Systems and Adaptive Learning (2 papers). Kumar Shridhar collaborates with scholars based in Switzerland, United States and Sweden. Kumar Shridhar's co-authors include Mrinmaya Sachan, Felix Laumann, Akshat Agarwal, Denis Kleyko, Tanmay Sinha, Manu Kapur, Mennatallah El‐Assady, Andrew McCallum, Bernhard Schoelkopf and Marcus Liwicki and has published in prestigious journals such as Research at the University of Copenhagen (University of Copenhagen), Repository for Publications and Research Data (ETH Zurich) and arXiv (Cornell University).

In The Last Decade

Kumar Shridhar

10 papers receiving 93 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kumar Shridhar Switzerland	7	75	14	10	10	7	13	98
Abhishek Singh India	5	93 1.2×	10 0.7×	13 1.3×	9 0.9×	18 2.6×	16	140
Prashant Shah United States	3	58 0.8×	6 0.4×	7 0.7×	5 0.5×	2 0.3×	5	79
Ameya Prabhu United Kingdom	5	115 1.5×	31 2.2×	10 1.0×	7 0.7×		11	133
P. Kavitha India	5	28 0.4×	19 1.4×	7 0.7×	8 0.8×	3 0.4×	30	64
Abdelrahaman Aly Belgium	5	76 1.0×	16 1.1×	26 2.6×	17 1.7×	3 0.4×	7	95
Matheus R. F. Mendonça Brazil	6	41 0.5×	5 0.4×	3 0.3×	5 0.5×	5 0.7×	10	68
Hongying Zan China	6	122 1.6×	15 1.1×	17 1.7×	3 0.3×	31 4.4×	50	169
Yunhui Long United States	5	122 1.6×	16 1.1×	12 1.2×	4 0.4×	2 0.3×	9	133
Tobias Falke Germany	7	224 3.0×	30 2.1×	22 2.2×	20 2.0×	16 2.3×	16	249
Roberta Răileanu Israel	4	76 1.0×	20 1.4×	6 0.6×	5 0.5×	1 0.1×	11	114

Countries citing papers authored by Kumar Shridhar

Since Specialization

Citations

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

Fields of papers citing papers by Kumar Shridhar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kumar Shridhar

This figure shows the co-authorship network connecting the top 25 collaborators of Kumar Shridhar. A scholar is included among the top collaborators of Kumar Shridhar 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 Kumar Shridhar. Kumar Shridhar 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.

Shridhar, Kumar, et al.. (2025). SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning. Research at the University of Copenhagen (University of Copenhagen). 9868–9880.

2.

Lyu, Qing, Kumar Shridhar, Chaitanya Malaviya, et al.. (2025). Calibrating Large Language Models with Sample Consistency. Proceedings of the AAAI Conference on Artificial Intelligence. 39(18). 19260–19268. 1 indexed citations

3.

Shridhar, Kumar, Koustuv Sinha, Andrew Cohen, et al.. (2024). The ART of LLM Refinement: Ask, Refine, and Trust. Repository for Publications and Research Data (ETH Zurich). 5872–5883. 2 indexed citations

4.

Shridhar, Kumar, et al.. (2023). Distilling Reasoning Capabilities into Smaller Language Models. 7059–7073. 24 indexed citations

5.

Shridhar, Kumar, et al.. (2023). Longtonotes: OntoNotes with Longer Coreference Chains. 1428–1442.

6.

Shridhar, Kumar, et al.. (2023). A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. 545–561. 9 indexed citations

7.

Shridhar, Kumar, et al.. (2022). Automatic Generation of Socratic Subquestions for Teaching Math Word Problems. 4136–4149. 19 indexed citations

8.

Shridhar, Kumar, et al.. (2021). Scaling Within Document Coreference to Long Texts. Repository for Publications and Research Data (ETH Zurich). 3921–3931. 9 indexed citations

9.

Shridhar, Kumar, et al.. (2020). End to End Binarized Neural Networks for Text Classification. 29–34. 14 indexed citations

10.

Kovács, György, et al.. (2019). Author Profiling Using Semantic and Syntactic Features : Notebook for PAN at CLEF 2019. SZTE Publicatio Repozitórium (University of Szeged). 2 indexed citations

11.

Kovács, György, et al.. (2019). Author Profiling using Semantic and Syntactic Features.. CLEF (Working Notes).

12.

Shridhar, Kumar, et al.. (2018). Bayesian Convolutional Neural Networks with Variational Inference. arXiv (Cornell University). 7 indexed citations

13.

Laumann, Felix & Kumar Shridhar. (2018). Bayesian Convolutional Neural Networks. arXiv (Cornell University). 11 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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