@inproceedings{song-etal-2026-retrieval,
title = "Retrieval-Augmented Generation for Symbolic Folk-Art Interpretation: Comparing Dense and Graph-Based Retrieval Using {K}orean Minhwa",
author = "Song, Minjun and
Kim, Sumin and
Kim, Junsung and
Lee, Yebeen and
Lee, Heung-No",
editor = "Ranaldi, Leonardo and
Pucci, Giulia and
Ranaldi, Federico and
Valentino, Marco and
Birch, Alexandra and
Zanzotto, Fabio Massimo",
booktitle = "The Proceedings of the Workshop on Open Reasoning Across Cultures Languages ({ORACLE})",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.oracle-main.17/",
pages = "257--275",
ISBN = "979-8-89176-483-5",
abstract = "Existing artwork-oriented retrieval-augmented generation (RAG) systems typically support visual understanding through contextual information such as artist metadata and historical background. Symbolic folk-art interpretation instead requires connecting visible motifs to culturally situated meanings. We study semiotic retrieval for this task in Korean minhwa, comparing dense semantic and graph-structured retrieval. We introduce SemioticRAG, which organizes symbolic knowledge through Barthesian Form, Concept, JointConcept, and Myth structures. Blind human evaluation shows that DenseRAG performs best overall, with SemioticRAG ranking second. Qualitative analysis indicates that SemioticRAG produces more explicit pathway-based symbolic compositions, while depending on Form-level grounding and graph construction quality. Overall, explicit semiotic structure changes how culturally grounded meanings are composed rather than uniformly improving interpretive quality."
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<abstract>Existing artwork-oriented retrieval-augmented generation (RAG) systems typically support visual understanding through contextual information such as artist metadata and historical background. Symbolic folk-art interpretation instead requires connecting visible motifs to culturally situated meanings. We study semiotic retrieval for this task in Korean minhwa, comparing dense semantic and graph-structured retrieval. We introduce SemioticRAG, which organizes symbolic knowledge through Barthesian Form, Concept, JointConcept, and Myth structures. Blind human evaluation shows that DenseRAG performs best overall, with SemioticRAG ranking second. Qualitative analysis indicates that SemioticRAG produces more explicit pathway-based symbolic compositions, while depending on Form-level grounding and graph construction quality. Overall, explicit semiotic structure changes how culturally grounded meanings are composed rather than uniformly improving interpretive quality.</abstract>
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%0 Conference Proceedings
%T Retrieval-Augmented Generation for Symbolic Folk-Art Interpretation: Comparing Dense and Graph-Based Retrieval Using Korean Minhwa
%A Song, Minjun
%A Kim, Sumin
%A Kim, Junsung
%A Lee, Yebeen
%A Lee, Heung-No
%Y Ranaldi, Leonardo
%Y Pucci, Giulia
%Y Ranaldi, Federico
%Y Valentino, Marco
%Y Birch, Alexandra
%Y Zanzotto, Fabio Massimo
%S The Proceedings of the Workshop on Open Reasoning Across Cultures Languages (ORACLE)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-483-5
%F song-etal-2026-retrieval
%X Existing artwork-oriented retrieval-augmented generation (RAG) systems typically support visual understanding through contextual information such as artist metadata and historical background. Symbolic folk-art interpretation instead requires connecting visible motifs to culturally situated meanings. We study semiotic retrieval for this task in Korean minhwa, comparing dense semantic and graph-structured retrieval. We introduce SemioticRAG, which organizes symbolic knowledge through Barthesian Form, Concept, JointConcept, and Myth structures. Blind human evaluation shows that DenseRAG performs best overall, with SemioticRAG ranking second. Qualitative analysis indicates that SemioticRAG produces more explicit pathway-based symbolic compositions, while depending on Form-level grounding and graph construction quality. Overall, explicit semiotic structure changes how culturally grounded meanings are composed rather than uniformly improving interpretive quality.
%U https://aclanthology.org/2026.oracle-main.17/
%P 257-275
Markdown (Informal)
[Retrieval-Augmented Generation for Symbolic Folk-Art Interpretation: Comparing Dense and Graph-Based Retrieval Using Korean Minhwa](https://aclanthology.org/2026.oracle-main.17/) (Song et al., ORACLE 2026)
ACL