Saloni Potdar

788 total citations
14 papers, 209 citations indexed

About

Saloni Potdar is a scholar working on Artificial Intelligence, Computer Networks and Communications and Management Information Systems. According to data from OpenAlex, Saloni Potdar has authored 14 papers receiving a total of 209 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 1 paper in Computer Networks and Communications and 1 paper in Management Information Systems. Recurrent topics in Saloni Potdar's work include Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Sentiment Analysis and Opinion Mining (3 papers). Saloni Potdar is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Sentiment Analysis and Opinion Mining (3 papers). Saloni Potdar collaborates with scholars based in United States and Italy. Saloni Potdar's co-authors include Feifei Zhai, Bowen Zhou, Bing Xiang, Lin Pan, Chung-Wei Hang, Avirup Sil, Mo Yu, Ming Tan, Lara J. Martin and Dakuo Wang and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, IRIS Research product catalog (Sapienza University of Rome) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Saloni Potdar

14 papers receiving 198 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saloni Potdar United States 7 178 38 24 11 8 14 209
Samuel Weinbach United States 2 176 1.0× 31 0.8× 42 1.8× 7 0.6× 8 1.0× 2 236
Emilio Sanchís Spain 10 243 1.4× 21 0.6× 20 0.8× 7 0.6× 15 1.9× 44 261
Nikita Nangia United States 5 268 1.5× 73 1.9× 23 1.0× 5 0.5× 6 0.8× 10 293
Jon Saad-Falcon United States 4 127 0.7× 52 1.4× 35 1.5× 3 0.3× 7 0.9× 9 170
Amir Kantor Israel 5 181 1.0× 40 1.1× 48 2.0× 7 0.6× 5 0.6× 14 237
Nils Blach Switzerland 3 106 0.6× 32 0.8× 22 0.9× 3 0.3× 5 0.6× 4 173
H. Niewiadomski Switzerland 4 106 0.6× 30 0.8× 21 0.9× 3 0.3× 5 0.6× 8 182
Xiaoxue Zang China 7 152 0.9× 54 1.4× 67 2.8× 9 0.8× 9 1.1× 23 223
Naveen Arivazhagan United States 3 214 1.2× 55 1.4× 28 1.2× 3 0.3× 8 1.0× 4 249
Michael Zhu United States 5 116 0.7× 17 0.4× 24 1.0× 10 0.9× 10 1.3× 14 151

Countries citing papers authored by Saloni Potdar

Since Specialization
Citations

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

Fields of papers citing papers by Saloni Potdar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saloni Potdar

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

All Works

14 of 14 papers shown
1.
2.
Pradeep, Ronak, Daniel Lee, Ali Mousavi, et al.. (2024). ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA Datasets with Large Language Models. 1176–1206. 3 indexed citations
3.
Conia, Simone, Daniel Lee, Min Li, et al.. (2024). Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs. IRIS Research product catalog (Sapienza University of Rome). 16343–16360. 2 indexed citations
4.
Xu, Panpan, et al.. (2023). The Second Workshop on Applied Machine Learning Management. 5859–5860. 1 indexed citations
5.
Qian, Cheng, et al.. (2022). Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants. 502–511. 1 indexed citations
6.
Qian, Cheng, et al.. (2022). Benchmarking Language-agnostic Intent Classification for Virtual Assistant Platforms. 69–76. 2 indexed citations
7.
Pan, Lin, Chung-Wei Hang, Avirup Sil, & Saloni Potdar. (2022). Improved Text Classification via Contrastive Adversarial Training. Proceedings of the AAAI Conference on Artificial Intelligence. 36(10). 11130–11138. 51 indexed citations
8.
Yang, Chenghao, Mo Yu, Bingsheng Yao, et al.. (2021). Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study. Transactions of the Association for Computational Linguistics. 9. 1032–1046. 9 indexed citations
9.
Pan, Lin, et al.. (2021). Multilingual BERT Post-Pretraining Alignment. 210–219. 12 indexed citations
10.
Pan, Lin, et al.. (2021). Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations. 304–310. 5 indexed citations
11.
Tan, Ming, Dakuo Wang, Yupeng Gao, et al.. (2019). Context-Aware Conversation Thread Detection in Multi-Party Chat. 6455–6460. 15 indexed citations
12.
Tan, Ming, Yang Yu, Haoyu Wang, et al.. (2019). Out-of-Domain Detection for Low-Resource Text Classification Tasks. 3564–3570. 26 indexed citations
13.
Zhai, Feifei, Saloni Potdar, Bing Xiang, & Bowen Zhou. (2017). Neural Models for Sequence Chunking. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 63 indexed citations
14.
Moon, Seungwhan, Saloni Potdar, & Lara J. Martin. (2014). Identifying Student Leaders from MOOC Discussion Forums through Language Influence. 15–20. 18 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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