Integration of cognitive tasks into artificial general intelligence test for large models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AIL6BFLWL" target="_blank" >RIV/00216208:11320/25:IL6BFLWL - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189562652&doi=10.1016%2fj.isci.2024.109550&partnerID=40&md5=00b8ba47af46f5d0d98a2eba1985bcfc" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189562652&doi=10.1016%2fj.isci.2024.109550&partnerID=40&md5=00b8ba47af46f5d0d98a2eba1985bcfc</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.isci.2024.109550" target="_blank" >10.1016/j.isci.2024.109550</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Integration of cognitive tasks into artificial general intelligence test for large models

Popis výsledku v původním jazyce

During the evolution of large models, performance evaluation is necessary for assessing their capabilities. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united framework for assessing the multidimensional intelligence of large models. In this perspective, we advocate for a comprehensive framework of cognitive science-inspired artificial general intelligence (AGI) tests, including crystallized, fluid, social, and embodied intelligence. The AGI tests consist of well-designed cognitive tests adopted from human intelligence tests, and then naturally encapsulates into an immersive virtual community. We propose increasing the complexity of AGI testing tasks commensurate with advancements in large models and emphasizing the necessity for the interpretation of test results to avoid false negatives and false positives. We believe that cognitive science-inspired AGI tests will effectively guide the targeted improvement of large models in specific dimensions of intelligence and accelerate the integration of large models into human society. © 2024 The Author(s)

Název v anglickém jazyce

Integration of cognitive tasks into artificial general intelligence test for large models

Popis výsledku anglicky

During the evolution of large models, performance evaluation is necessary for assessing their capabilities. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united framework for assessing the multidimensional intelligence of large models. In this perspective, we advocate for a comprehensive framework of cognitive science-inspired artificial general intelligence (AGI) tests, including crystallized, fluid, social, and embodied intelligence. The AGI tests consist of well-designed cognitive tests adopted from human intelligence tests, and then naturally encapsulates into an immersive virtual community. We propose increasing the complexity of AGI testing tasks commensurate with advancements in large models and emphasizing the necessity for the interpretation of test results to avoid false negatives and false positives. We believe that cognitive science-inspired AGI tests will effectively guide the targeted improvement of large models in specific dimensions of intelligence and accelerate the integration of large models into human society. © 2024 The Author(s)

Druh

J_SC - Článek v periodiku v databázi SCOPUS

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

—

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

iScience

ISSN

2589-0042

e-ISSN

—

Svazek periodika

27

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85189562652