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Hauptverfasser: Tsutsumi, Ayuto, Kohita, Ryosuke
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2605.12905
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author Tsutsumi, Ayuto
Kohita, Ryosuke
author_facet Tsutsumi, Ayuto
Kohita, Ryosuke
contents A scene of two people in the rain can convey hope and warmth in a reunion story or sorrow and finality in a farewell story. We investigate this context-dependent nature of image meaning and its implications for retrieval. Our key observation is that context dependency correlates with semantic abstraction: concrete elements (objects, actions) remain stable across contexts, while abstract elements (atmosphere, intent) shift with context. We operationalize this as the L1--L4 framework, organizing image semantics from context-independent (L1) to maximally context-dependent (L4). Using synthetic story contexts and queries for controlled evaluation, we examine how injecting narrative context into embeddings affects retrieval across abstraction levels. Concrete queries are retrievable without context, while abstract levels increasingly depend on narrative grounding. Where context is injected also matters, with image-side enrichment proving particularly effective. The most abstract level, however, remains challenging even with full context, highlighting context-dependent image retrieval as an important open problem. Our framework and findings lay groundwork toward retrieval systems that handle the context-dependent meanings images acquire in narrative settings.
format Preprint
id arxiv_https___arxiv_org_abs_2605_12905
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Same Image, Different Meanings: Toward Retrieval of Context-Dependent Meanings
Tsutsumi, Ayuto
Kohita, Ryosuke
Information Retrieval
A scene of two people in the rain can convey hope and warmth in a reunion story or sorrow and finality in a farewell story. We investigate this context-dependent nature of image meaning and its implications for retrieval. Our key observation is that context dependency correlates with semantic abstraction: concrete elements (objects, actions) remain stable across contexts, while abstract elements (atmosphere, intent) shift with context. We operationalize this as the L1--L4 framework, organizing image semantics from context-independent (L1) to maximally context-dependent (L4). Using synthetic story contexts and queries for controlled evaluation, we examine how injecting narrative context into embeddings affects retrieval across abstraction levels. Concrete queries are retrievable without context, while abstract levels increasingly depend on narrative grounding. Where context is injected also matters, with image-side enrichment proving particularly effective. The most abstract level, however, remains challenging even with full context, highlighting context-dependent image retrieval as an important open problem. Our framework and findings lay groundwork toward retrieval systems that handle the context-dependent meanings images acquire in narrative settings.
title Same Image, Different Meanings: Toward Retrieval of Context-Dependent Meanings
topic Information Retrieval
url https://arxiv.org/abs/2605.12905