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Evidence record 3375 · automatically gathered

Benchmarks for Vision-Language Models in Urban Perception Should Be Reliability-Aware and Negotiated

Vision-language models (VLMs) are increasingly used to generate structured descriptions of street-level imagery for tasks such as streetscape auditing, mapping, and public consultation. These uses combine observable attributes with appraisal categories, and the human targets are often distributions of judgments with disagreement and explicit non-response. This paper argues that benchmarking VLMs for urban perception should treat disagreement and abstention as measurement outcomes, report inter-a

Record details

Published: 30 May 2026
Source: arXiv
Category: Research
Topics: Transparency
Retrieved: 14 July 2026

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These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (30 May 2026), “Benchmarks for Vision-Language Models in Urban Perception Should Be Reliability-Aware and Negotiated,” evidence record 3375, https://ethics.ai/record/3375 (originally published by arXiv).

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