CV-Probes: Studying the interplay of lexical and world knowledge in visually grounded verb understanding
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F26%3A0199796" target="_blank" >RIV/00216305:26230/26:0199796 - isvavai.cz</a>
Result on the web
<a href="https://escholarship.org/content/qt3h83566r/qt3h83566r.pdf?v=lg" target="_blank" >https://escholarship.org/content/qt3h83566r/qt3h83566r.pdf?v=lg</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
CV-Probes: Studying the interplay of lexical and world knowledge in visually grounded verb understanding
Original language description
How do vision-language (VL) transformer models ground verb phrases and do they integrate contextual and world knowledge in this process? We introduce the CV-Probes dataset, containing image-caption pairs involving verb phrases that require both social knowledge and visual context to interpret (e.g., ‘beg’), as well as pairs involving verb phrases that can be grounded based on information directly available in the image (e.g., “sit”). We show that VL models struggle to ground VPs that are strongly context-dependent. Further analysis using explainable AI techniques shows that such models may not pay sufficient attention to the verb token in the captions. Our results suggest a need for improved methodologies in VL model training and evaluation. The code and dataset will be available https://github.com/ivana-13/CV-Probes.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů