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cs.CL2026
Humans vs Vision-Language Models: A Unified Measure of Narrative Coherence
Nikolai Ilinykh, Hyewon Jang, Shalom Lappin +2
We study narrative coherence in visually grounded stories by comparing human-written narratives with those generated by vision-language models (VLMs) on the Visual Writing Prompts…
cs.CL2025
Surprisal reveals diversity gaps in image captioning and different scorers change the story
Nikolai Ilinykh, Simon Dobnik
We quantify linguistic diversity in image captioning with surprisal variance - the spread of token-level negative log-probabilities within a caption set. On the MSCOCO test set, we…
cs.CL2025
Coreference as an indicator of context scope in multimodal narrative
Nikolai Ilinykh, Shalom Lappin, Asad Sayeed +1
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…