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cs.CV2026
Benchmarks for Vision-Language Models in Urban Perception Should Be Reliability-Aware and Negotiated
Rashid Mushkani
Vision-language models (VLMs) are increasingly used to generate structured descriptions of street-level imagery for tasks such as streetscape auditing, mapping, and public consulta…
cs.CV2025
Do Vision-Language Models See Urban Scenes as People Do? An Urban Perception Benchmark
Rashid Mushkani
Understanding how people read city scenes can inform design and planning. We introduce a small benchmark for testing vision-language models (VLMs) on urban perception using 100 Mon…
cs.CV2025
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
Rashid Mushkani, Shravan Nayak, Hugo Berard +3
We introduce the Local Intersectional Visual Spaces (LIVS) dataset, a benchmark for multi-criteria alignment, developed through a two-year participatory process with 30 community o…