Introduction to the Special Issue on Large Action Models (LAMs): Theory, Implementation, and Applications
TL;DR
Five contributions addressing key challenges in LAM research are brought together, including safety and robustness against jailbreak and adversarial attacks, semantic-perceptual integration for robotic manipulation, efficient deployment on edge devices, and natural-language-driven decision-making for networked systems.
Abstract
Large Action Models (LAMs) extend the capabilities of AI systems beyond text generation toward perception, reasoning, and action, enabling applications across robotics, autonomous systems, smart manufacturing, healthcare, and the Internet of Things. This Special Issue of ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) brings together five contributions addressing key challenges in LAM research, including safety and robustness against jailbreak and adversarial attacks, semantic-perceptual integration for robotic manipulation, efficient deployment on edge devices, and natural-language-driven decision-making for networked systems. Together, these papers span the theoretical, implementation, and application dimensions of LAMs, offering both practical solutions and a foundation for future research toward LAM-based systems that are safe, efficient, and reliably grounded in action.