@inproceedings{brown-etal-2024-interactive-toolkit,
title = "An Interactive Toolkit for Approachable {NLP}",
author = "Brown, AriaRay and
Steuer, Julius and
Mosbach, Marius and
Klakow, Dietrich",
editor = {Al-azzawi, Sana and
Biester, Laura and
Kov{\'a}cs, Gy{\"o}rgy and
Marasovi{\'c}, Ana and
Mathur, Leena and
Mieskes, Margot and
Weissweiler, Leonie},
booktitle = "Proceedings of the Sixth Workshop on Teaching NLP",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.teachingnlp-1.17",
pages = "119--127",
abstract = "We present a novel tool designed for teaching and interfacing the information-theoretic modeling abilities of large language models. The Surprisal Toolkit allows students from diverse linguistic and programming backgrounds to learn about measures of information theory and natural language processing (NLP) through an online interactive tool. In addition, the interface provides a valuable research mechanism for obtaining measures of surprisal. We implement the toolkit as part of a classroom tutorial in three different learning scenarios and discuss the overall receptive student feedback. We suggest this toolkit and similar applications as resourceful supplements to instruction in NLP topics, especially for the purpose of balancing conceptual understanding with technical instruction, grounding abstract topics, and engaging students with varying coding abilities.",
}
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%0 Conference Proceedings
%T An Interactive Toolkit for Approachable NLP
%A Brown, AriaRay
%A Steuer, Julius
%A Mosbach, Marius
%A Klakow, Dietrich
%Y Al-azzawi, Sana
%Y Biester, Laura
%Y Kovács, György
%Y Marasović, Ana
%Y Mathur, Leena
%Y Mieskes, Margot
%Y Weissweiler, Leonie
%S Proceedings of the Sixth Workshop on Teaching NLP
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F brown-etal-2024-interactive-toolkit
%X We present a novel tool designed for teaching and interfacing the information-theoretic modeling abilities of large language models. The Surprisal Toolkit allows students from diverse linguistic and programming backgrounds to learn about measures of information theory and natural language processing (NLP) through an online interactive tool. In addition, the interface provides a valuable research mechanism for obtaining measures of surprisal. We implement the toolkit as part of a classroom tutorial in three different learning scenarios and discuss the overall receptive student feedback. We suggest this toolkit and similar applications as resourceful supplements to instruction in NLP topics, especially for the purpose of balancing conceptual understanding with technical instruction, grounding abstract topics, and engaging students with varying coding abilities.
%U https://aclanthology.org/2024.teachingnlp-1.17
%P 119-127
Markdown (Informal)
[An Interactive Toolkit for Approachable NLP](https://aclanthology.org/2024.teachingnlp-1.17) (Brown et al., TeachingNLP-WS 2024)
ACL
- AriaRay Brown, Julius Steuer, Marius Mosbach, and Dietrich Klakow. 2024. An Interactive Toolkit for Approachable NLP. In Proceedings of the Sixth Workshop on Teaching NLP, pages 119–127, Bangkok, Thailand. Association for Computational Linguistics.