bot.zen at LangLearn: regressing towards interpretability

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00133120" target="_blank" >RIV/00216224:14330/23:00133120 - isvavai.cz</a>

Result on the web

<a href="https://ceur-ws.org/Vol-3473/paper21.pdf" target="_blank" >https://ceur-ws.org/Vol-3473/paper21.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

bot.zen at LangLearn: regressing towards interpretability

Original language description

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.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian

ISBN

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ISSN

1613-0073

e-ISSN

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Number of pages

5

Pages from-to

1-5

Publisher name

CEUR.org

Place of publication

Parma

Event location

Parma

Event date

Jan 1, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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