LIGHT: Deployable Small Foundation Models

Foundation models have achieved remarkable performance across language, vision, and multimodal tasks, but their deployment remains challenging due to their size, computational requirements, and limited controllability. This workshop explores the emerging transition from large foundation models to compact, trustworthy, and deployable AI systems. It focuses on knowledge distillation, compression, quantization, and small foundation models. By bringing together researchers from machine learning, AI systems, trustworthy AI, and industrial deployment, the workshop aims to foster a common research agenda for efficient and trustworthy AI systems capable of operating under real-world constraints.