Generative AI and the end of corpus-assisted data-driven learning? Not so fast!

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00139271" target="_blank" >RIV/00216224:14330/23:00139271 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.acorp.2023.100066" target="_blank" >http://dx.doi.org/10.1016/j.acorp.2023.100066</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.acorp.2023.100066" target="_blank" >10.1016/j.acorp.2023.100066</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Generative AI and the end of corpus-assisted data-driven learning? Not so fast!

Popis výsledku v původním jazyce

This article explores the potential advantages of corpora over generative artificial intelligence (GenAI) in understanding language patterns and usage, while also acknowledging the potential of GenAI to address some of the main shortcomings of corpus-based data-driven learning (DDL). One of the main advantages of corpora is that we know exactly the domain of texts from which the corpus data is derived, something that we cannot track from current large language models underlying applications like ChatGPT. We know the texts that make up large general corpora such as BNC2014 and BAWE, and can even extract full texts from these corpora if needed. Corpora also allow for more nuanced analysis of language patterns, including the statistics behind multi-word units and collocations, which can be difficult for GenAI to handle. However, it is important to note that GenAI has its own strengths in advancing our understanding of language-in-use that corpora, to date, have struggled with. We therefore argue that by combining corpus and GenAI approaches, language learners can gain a more comprehensive understanding of how language works in different contexts than is currently possible using only a single approach.

Název v anglickém jazyce

Generative AI and the end of corpus-assisted data-driven learning? Not so fast!

Popis výsledku anglicky

This article explores the potential advantages of corpora over generative artificial intelligence (GenAI) in understanding language patterns and usage, while also acknowledging the potential of GenAI to address some of the main shortcomings of corpus-based data-driven learning (DDL). One of the main advantages of corpora is that we know exactly the domain of texts from which the corpus data is derived, something that we cannot track from current large language models underlying applications like ChatGPT. We know the texts that make up large general corpora such as BNC2014 and BAWE, and can even extract full texts from these corpora if needed. Corpora also allow for more nuanced analysis of language patterns, including the statistics behind multi-word units and collocations, which can be difficult for GenAI to handle. However, it is important to note that GenAI has its own strengths in advancing our understanding of language-in-use that corpora, to date, have struggled with. We therefore argue that by combining corpus and GenAI approaches, language learners can gain a more comprehensive understanding of how language works in different contexts than is currently possible using only a single approach.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Applied Corpus Linguistics

ISSN

2666-7991

e-ISSN

—

Svazek periodika

3

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

4

Strana od-do

1-4

Kód UT WoS článku

001403155600007

EID výsledku v databázi Scopus

2-s2.0-85174986819