Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects
Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects
著者: Agnese Chiatti, Sara Bernardini, Lara Shibelski Godoy Piccolo, Viola Schiaffonati, Matteo Matteucci
分類: cs.CV, cs.AI, cs.CY, cs.HC, cs.RO
原文アブストラクト
The rapid adoption of Vision Language Models (VLMs), pre-trained on large image-text and video-text datasets, calls for protecting and informing users about when to trust these systems. This survey reviews studies on trust dynamics in user-VLM interactions, through a multi-disciplinary taxonomy encompassing different cognitive science capabilities, collaboration modes, and agent behaviours. Literature insights and findings from a workshop with prospective VLM users inform preliminary requirements for future VLM trust studies.