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Evidence record 1036 · automatically gathered

Bridging Geographic Bias in Urban Streetscape Inference via Lifelong Learning with Visual-Semantic Pivoting

Visual perception of urban streetscapes underpins evidence-based decisions in landscape planning, public health, and place-making. Yet models trained on a few well-photographed metropolises systematically misjudge underrepresented districts, propagating geographic bias into downstream policy. We address this gap with HVSP-LL, a lifelong learning framework that couples a stratified visual-semantic pivoting module with an equity-aware rehearsal mechanism. The pivoting module organises landscape co

Record details

Published: 13 June 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Regulation · Healthcare
Retrieved: 14 July 2026

source-onlyevidence status

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.

Shared topic: Bias & fairness · Shared topic: Regulation

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Shared topic: Bias & fairness · Shared topic: Regulation

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Shared topic: Bias & fairness · Shared topic: Regulation

Constance Viehbeck

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How to cite this record

ethics.ai (13 June 2026), “Bridging Geographic Bias in Urban Streetscape Inference via Lifelong Learning with Visual-Semantic Pivoting,” evidence record 1036, https://ethics.ai/record/1036 (originally published by arXiv).

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