Papers by Dhruv Shah
Hindi History Note Generation with Unsupervised Extractive Summarization (2020.aacl-srw)
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| Challenge: | Existing methods to extract summaries from Hindi textbooks perform poorly in English. |
| Approach: | They propose to use unsupervised methods to extract single document summarization from Hindi history textbooks. |
| Outcome: | The proposed tool could help students memorize a text summary for the exam . prior studies show that the proposed methods perform poorly on Hindi documents . |
Declarative Techniques for NL Queries over Heterogeneous Data (2025.emnlp-industry)
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Elham Khabiri, Jeffrey O. Kephart, Fenno F. Heath Iii, Srideepika Jayaraman, Yingjie Li, Fateh A. Tipu, Dhruv Shah, Achille Fokoue, Anu Bhamidipaty
| Challenge: | In many industrial settings, users wish to ask questions in natural language . however, these applications do not cope with data source heterogeneity that typifies such environments. |
| Approach: | They propose a declarative approach to handling data heterogeneity in industrial settings . they simulate the heterogenity of industrial environments by adding two extensions of the popular Spider benchmark dataset . |
| Outcome: | The proposed approach copes with data source heterogeneity better than state-of-the-art systems. |