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bot.zen at LangLearn: regressing towards interpretability
Conference proceeding   Open access  Peer reviewed

bot.zen at LangLearn: regressing towards interpretability

Egon Waldemar Stemle, Martina Tebaldini, Francesca Bonanni, Filippo Pellegrino, Paolo Brasolin, Greta Franzini, Jennifer-Carmen Frey, Olga Lopopolo and Stefania Spina
Proceedings of the Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2023), Parma, Italy, September 7th-8th, 2023
EVALITA 2023: 8th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian (Parma, 07/09/2023 - 08/09/2023)
2023
Handle:
https://hdl.handle.net/10863/36636

Abstract

This article describes the bot.zen system that participated in the Language Learning Development (LangLearn) shared task of the EVALITA 2023 campaign. We developed a simple machine learning system with good interpretability for later use, and used the shared task as an opportunity to provide Master’s students with hands-on training and practical experience in NLP.
pdf
paper21240.91 kBDownloadView
CC BY V4.0,  Open Access
url
https://www.evalita.it/campaigns/evalita-2023/View
url
https://ceur-ws.org/Vol-3473/paper21.pdfView

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