@inproceedings{da-silva-etal-2026-persona,
title = "Persona Prompting in Multimodal Urban Perception: Descriptive Convergence and Interpretive Variation",
author = "da Silva, Neemias B and
Ratto, Matt and
Delgado, Myriam and
Minetto, Rodrigo and
Silver, Daniel and
Silva, Thiago H.",
editor = "Xu, Shanshan and
T.Y.S.S., Santosh and
Kurniawan, Kemal and
Peng, Siyao and
Wallbridge, Sarenne and
Koto, Fajri and
Dziri, Nouha and
Plank, Barbara",
booktitle = "Proceedings of the First Workshop on Pluralistic {AI} {NLP}: Diversity-aware, Sociotechnical, Responsible Alignment ({PANDORA} 2026)",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.pandora-1.17/",
pages = "301--318",
ISBN = "979-8-89176-484-2",
abstract = "This study examines how persona prompting shapes language generated by two multimodal large language models in urban perception, a setting for examining subjective interpretations of shared visual evidence. We organize outputs into three functional layers: descriptive grounding (captions), intermediate semantic layer (perception tags), and interpretive framing (justifications). Using approximately 60,000 persona-conditioned annotations from each of two MLLMs, Qwen3-VL and Gemma4, we find that captions converge strongly across persona profiles and show only small attribute-associated differences. Justifications vary substantially more: economic status produces the largest difference in both models, with political orientation and personality also prominent. Paired image-level comparisons confirm larger justification than caption differences for these three attributes. For perception tags, personas sharing the same attribute level produce more similar tag sets than personas with different attribute levels, with the largest separation observed for economic status. Exploratory topic analysis further suggests persona-specific evaluative emphasis. Across models, profile-pair similarity patterns are strongly correlated for all three output types, although agreement is lowest for justifications. Overall, persona prompting affects interpretive framing more strongly than descriptive grounding."
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%0 Conference Proceedings
%T Persona Prompting in Multimodal Urban Perception: Descriptive Convergence and Interpretive Variation
%A da Silva, Neemias B.
%A Ratto, Matt
%A Delgado, Myriam
%A Minetto, Rodrigo
%A Silver, Daniel
%A Silva, Thiago H.
%Y Xu, Shanshan
%Y T.Y.S.S., Santosh
%Y Kurniawan, Kemal
%Y Peng, Siyao
%Y Wallbridge, Sarenne
%Y Koto, Fajri
%Y Dziri, Nouha
%Y Plank, Barbara
%S Proceedings of the First Workshop on Pluralistic AI NLP: Diversity-aware, Sociotechnical, Responsible Alignment (PANDORA 2026)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-484-2
%F da-silva-etal-2026-persona
%X This study examines how persona prompting shapes language generated by two multimodal large language models in urban perception, a setting for examining subjective interpretations of shared visual evidence. We organize outputs into three functional layers: descriptive grounding (captions), intermediate semantic layer (perception tags), and interpretive framing (justifications). Using approximately 60,000 persona-conditioned annotations from each of two MLLMs, Qwen3-VL and Gemma4, we find that captions converge strongly across persona profiles and show only small attribute-associated differences. Justifications vary substantially more: economic status produces the largest difference in both models, with political orientation and personality also prominent. Paired image-level comparisons confirm larger justification than caption differences for these three attributes. For perception tags, personas sharing the same attribute level produce more similar tag sets than personas with different attribute levels, with the largest separation observed for economic status. Exploratory topic analysis further suggests persona-specific evaluative emphasis. Across models, profile-pair similarity patterns are strongly correlated for all three output types, although agreement is lowest for justifications. Overall, persona prompting affects interpretive framing more strongly than descriptive grounding.
%U https://aclanthology.org/2026.pandora-1.17/
%P 301-318
Markdown (Informal)
[Persona Prompting in Multimodal Urban Perception: Descriptive Convergence and Interpretive Variation](https://aclanthology.org/2026.pandora-1.17/) (da Silva et al., PANDORA 2026)
ACL
- Neemias B da Silva, Matt Ratto, Myriam Delgado, Rodrigo Minetto, Daniel Silver, and Thiago H. Silva. 2026. Persona Prompting in Multimodal Urban Perception: Descriptive Convergence and Interpretive Variation. In Proceedings of the First Workshop on Pluralistic AI NLP: Diversity-aware, Sociotechnical, Responsible Alignment (PANDORA 2026), pages 301–318, Budapest, Hungary. Association for Computational Linguistics.