Saurav Jha
2024
Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy
Aditya Joshi
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Jake Renzella
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Pushpak Bhattacharyya
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Saurav Jha
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Xiangyu Zhang
Proceedings of the Sixth Workshop on Teaching NLP
While deep learning approaches represent the state-of-the-art of natural language processing (NLP) today, classical algorithms and approaches still find a place in NLP textbooks and courses of recent years. This paper discusses the perspectives of conveners of two introductory NLP courses taught in Australia and India, and examines how classical and deep learning approaches can be balanced within the lecture plan and assessments of the courses. We also draw parallels with the objects-first and objects-later debate in CS1 education. We observe that teaching classical approaches adds value to student learning by building an intuitive understanding of NLP problems, potential solutions, and even deep learning models themselves. Despite classical approaches not being state-of-the-art, the paper makes a case for their inclusion in NLP courses today.
2017
Reference Scope Identification for Citances Using Convolutional Neural Networks
Saurav Jha
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Aanchal Chaurasia
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Akhilesh Sudhakar
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Anil Kumar Singh
Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017)
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Co-authors
- Aanchal Chaurasia 1
- Akhilesh Sudhakar 1
- Anil Kumar Singh 1
- Aditya Joshi 1
- Jake Renzella 1
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