English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Although large language models (LLMs) are often pre-trained on large-scalemultilingual texts, their reasoning abilities and real-world knowledge aremainly evaluated based on English datasets. Assessing LLM capabilities beyondEnglish is increasingly vital but hindered due to the lack of suitabledatasets. In this work, we introduce IndoMMLU, the first multi-task languageunderstanding benchmark for Indonesian culture and languages, which consists ofquestions from primary school to university entrance exams in Indonesia. Byemploying professional teachers, we obtain 14,981 questions across 64 tasks andeducation levels, with 46% of the questions focusing on assessing proficiencyin the Indonesian language and knowledge of nine local languages and culturesin Indonesia. Our empirical evaluations show that GPT-3.5 only manages to passthe Indonesian primary school level, with limited knowledge of local Indonesianlanguages and culture. Other smaller models such as BLOOMZ and Falcon performat even lower levels.

Large Language Models Only Pass Primary School Exams in Indonesia: A Comprehensive Test on IndoMMLU