LangXAI is a framework that integrates Explainable Artificial Intelligence
(XAI) with advanced vision models to generate textual explanations for visual
recognition tasks. Despite XAI advancements, an understanding gap persists for
end-users with limited domain knowledge in artificial intelligence and computer
vision. LangXAI addresses this by furnishing text-based explanations for
classification, object detection, and semantic segmentation model outputs to
end-users. Preliminary results demonstrate LangXAI's enhanced plausibility,
with high BERTScore across tasks, fostering a more transparent and reliable AI
framework on vision tasks for end-users.

LangXAI 是一个框架，将可解释的人工智能 (XAI) 与先进的视觉模型相结合，为视觉识别任务生成文本解释。通过为最终用户提供分类、目标检测和语义分割模型输出的基于文本的解释，LangXAI 填补了人工智能和计算机视觉领域知识有限的最终用户的理解差距。初步结果表明，LangXAI 具有更高的 BERT 分数，增强了其可信度和透明度，为最终用户提供了一个更加透明可靠的视觉任务的人工智能框架。