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        <title>No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding</title>
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        <namePart type="given">Vynska</namePart>
        <namePart type="given">Amalia</namePart>
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    <name type="personal">
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    <abstract>Understanding culture requires reasoning across context, tradition, and implicit social knowledge, far beyond recalling isolated facts. Yet most culturally focused question answering (QA) benchmarks rely on singlehop questions, which may allow models to exploit shallow cues rather than demonstrate genuine cultural reasoning. In this work, we introduce ID-MoCQA, the first large-scale multi-hop QA dataset for assessing the cultural understanding of large language models (LLMs), grounded in Indonesian traditions and available in both English and Indonesian. We present a new framework that systematically transforms single-hop cultural questions into multi-hop reasoning chains spanning six clue types (e.g., commonsense, temporal, geographical). Our multi-stage validation pipeline, combining expert review and LLM-as-a-judge filtering, ensures high-quality question-answer pairs. Our evaluation across state-of-the-art models reveals substantial gaps in cultural reasoning, particularly in tasks requiring nuanced inference. ID-MoCQA provides a challenging and essential benchmark for advancing the cultural competency of LLMs.1</abstract>
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    <identifier type="doi">10.1162/tacl.a.726</identifier>
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%0 Journal Article
%T No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding
%A Permadi, Vynska Amalia
%A Tan, Xingwei
%A Moosavi, Nafise Sadat
%A Aletras, Nikolaos
%J Transactions of the Association for Computational Linguistics
%D 2026
%V 14
%I MIT Press
%C Cambridge, MA
%F permadi-etal-2026-shortcuts
%X Understanding culture requires reasoning across context, tradition, and implicit social knowledge, far beyond recalling isolated facts. Yet most culturally focused question answering (QA) benchmarks rely on singlehop questions, which may allow models to exploit shallow cues rather than demonstrate genuine cultural reasoning. In this work, we introduce ID-MoCQA, the first large-scale multi-hop QA dataset for assessing the cultural understanding of large language models (LLMs), grounded in Indonesian traditions and available in both English and Indonesian. We present a new framework that systematically transforms single-hop cultural questions into multi-hop reasoning chains spanning six clue types (e.g., commonsense, temporal, geographical). Our multi-stage validation pipeline, combining expert review and LLM-as-a-judge filtering, ensures high-quality question-answer pairs. Our evaluation across state-of-the-art models reveals substantial gaps in cultural reasoning, particularly in tasks requiring nuanced inference. ID-MoCQA provides a challenging and essential benchmark for advancing the cultural competency of LLMs.1
%R 10.1162/tacl.a.726
%U https://aclanthology.org/2026.tacl-1.56/
%U https://doi.org/10.1162/tacl.a.726
%P 1243-1265

Markdown (Informal)

[No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding](https://aclanthology.org/2026.tacl-1.56/) (Permadi et al., TACL 2026)

• No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding (Permadi et al., TACL 2026)

ACL

• Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi, and Nikolaos Aletras. 2026. No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding. Transactions of the Association for Computational Linguistics, 14:1243–1265.