Lucas Kabela
2021
Contemporary NLP Modeling in Six Comprehensive Programming Assignments
Greg Durrett
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Jifan Chen
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Shrey Desai
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Tanya Goyal
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Lucas Kabela
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Yasumasa Onoe
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Jiacheng Xu
Proceedings of the Fifth Workshop on Teaching NLP
We present a series of programming assignments, adaptable to a range of experience levels from advanced undergraduate to PhD, to teach students design and implementation of modern NLP systems. These assignments build from the ground up and emphasize full-stack understanding of machine learning models: initially, students implement inference and gradient computation by hand, then use PyTorch to build nearly state-of-the-art neural networks using current best practices. Topics are chosen to cover a wide range of modeling and inference techniques that one might encounter, ranging from linear models suitable for industry applications to state-of-the-art deep learning models used in NLP research. The assignments are customizable, with constrained options to guide less experienced students or open-ended options giving advanced students freedom to explore. All of them can be deployed in a fully autogradable fashion, and have collectively been tested on over 300 students across several semesters.
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Co-authors
- Greg Durrett 1
- Jifan Chen 1
- Shrey Desai 1
- Tanya Goyal 1
- Yasumasa Onoe 1
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