面向色觉缺陷的情境感知支持：一种融合大语言模型与增强现实的方法
Towards Context-aware Support for Color Vision Deficiency: An Approach Integrating LLM and AR
AI总结：
本文针对色觉缺陷人群的日常辨色困难，提出一种结合增强现实情境捕获与多模态大语言模型推理的自主辅助应用，并通过多场景用户实验验证其有效性与普适性。
摘要：
色觉缺陷人群在区分红色和绿色等颜色时常常面临困难，这可能使日常任务复杂化，并需要使用辅助工具或调整环境。当前的支持工具主要集中于基于呈现的辅助手段，例如iPhone辅助功能设置中的色觉模式。然而，提供情境感知的支持（例如判断肉类的熟度）仍然是一个挑战，因为针对特定任务的解决方案无法以经济高效的方式覆盖所有可能的场景。为了解决这一问题，本文提出了一种提供情境化自主辅助的应用程序。该应用程序主要由以下部分组成：（i）一个增强现实界面，用于高效地捕获情境；（ii）一个基于多模态大语言模型的推理器，用于对情境进行认知化处理，进而推理出适当的支持内容。针对两名色觉缺陷用户在五个不同场景中进行的初步用户实验证明了该应用程序的有效性和普适性。
英文摘要：
People with color vision deficiency often face challenges in distinguishing colors such as red and green, which can complicate daily tasks and require the use of assistive tools or environmental adjustments. Current support tools mainly focus on presentation-based aids, like the color vision modes found in iPhone accessibility settings. However, offering context-aware support, like indicating the doneness of meat, remains a challenge since task-specific solutions are not cost-effective for all possible scenarios. To address this, our paper proposes an application that provides contextual and autonomous assistance. This application is mainly composed of: (i) an augmented reality interface that efficiently captures context; and (ii) a multi-modal large language model-based reasoner that serves to cognitize the context and then reason about the appropriate support contents. Preliminary user experiments with two color vision deficient users across five different scenarios have demonstrated the effectiveness and universality of our application.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
