WasteAssistant: Regulation-Guided Visual Question Answering Framework for Intelligent Waste Segregation and Sustainable Managemen
Efficient waste segregation is critical for sustainable urban management and environmental governance. Existing automated systems are limited by single-modality visual processing, insufficient contextual understanding, and weak regulatory alignment. To address these issues, we propose a language-guided vision-AI framework that integrates vision-language models and multimodal large language models for joint visual-linguistic reasoning. This framework implements a visual question answering paradig
Record details
Published: 12 July 2026
Source: arXiv
Category: Research
Topics: Regulation · Safety & alignment · Environment
Retrieved: 14 July 2026
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ethics.ai (12 July 2026), “WasteAssistant: Regulation-Guided Visual Question Answering Framework for Intelligent Waste Segregation and Sustainable Managemen,” evidence record 35, https://ethics.ai/record/35 (originally published by arXiv).
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