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arXiv · 2503.05298

Coreference as an indicator of context scope in multimodal narrative

Nikolai Ilinykh·Shalom Lappin·Asad Sayeed·Sharid Loáiciga
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Abstract

We demonstrate that large multimodal language models differ substantially from humans in the distribution of coreferential expressions in a visual storytelling task. We introduce a number of metrics to quantify the characteristics of coreferential patterns in both human- and machine-written texts. Humans distribute coreferential expressions in a way that maintains consistency across texts and images, interleaving references to different entities in a highly varied way. Machines are less able to track mixed references, despite achieving perceived improvements in generation quality. Materials, metrics, and code for our study are available at https://github.com/GU-CLASP/coreference-context-scope.

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Nikolai Ilinykh, Shalom Lappin, Asad Sayeed, Sharid Loáiciga. 2025-03-07. Coreference as an indicator of context scope in multimodal narrative. https://arxiv.org/abs/2503.05298

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