SLM-Agents: 1st Workshop on SLMs for Agentic Systems
Abstract
This workshop is dedicated to small language models (SLMs) as the foundation of agentic AI systems. Although large language models (LLMs) have demonstrated remarkable capabilities, their dependence on cloud infrastructure creates fundamental barriers to deployment in agentic pipelines latency, privacy, connectivity, and substantial computational cost. SLMs offer a compelling alternative: recent studies argue that SLMs, not LLMs, might be the right option for the repetitive, narrowly scoped sub-tasks that dominate real agentic workloads [15]. SLMs make it possible for autonomous AI agents to plan, reason, and act directly on resource-constrained devices such as smartphones, IoT systems, robotics platforms, and embedded systems. The workshop sits at the intersection of three rapidly evolving fields: (1) efficient language model architectures and compression techniques, (2) agentic AI systems capable of autonomous reasoning and tool use, and (3) edge computing and on-device deployment.