AI RESEARCH
Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistants
arXiv CS.CL
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ArXi:2508.16070v4 Announce Type: replace Approximately 283M people worldwide live with visual impairments, motivating increasing research into leveraging Visual Language Models (VLMs) to develop effective walking assistance systems for blind and low vision individuals. However, existing VLMs in walking assistant task often have outputs that contain considerable redundancy and extraneous details, adversely affecting users' ability to accurately assess their surroundings.