The 1st International Workshop on LLM-Driven Agents

- Unleashing the Power of LLM-Driven Agents: From Theory to Real-World Applications

1. Motivation and Scope

Large Language Models (LLMs) have evolved from powerful text generators to autonomous agents capable of decision-making, tool use, and complex task execution. The emergence of LLM-driven agents represents a paradigm shift in AI—where foundation models serve not just as passive engines but as interactive, goal-directed systems. Despite exciting progress, fundamental theoretical challenges remain: What are the formal models of LLM-driven agency? How can we ensure safety, alignment, planning consistency, and memory grounding? Moreover, the transition from lab settings to real-world applications in domains like software engineering, healthcare, education, and robotics raises additional questions about robustness, deployment, evaluation, and cost-efficiency.

This workshop aims to bridge the gap between theory and practice by uniting researchers and practitioners working on various aspects of LLM-driven agents.

2. Topics of Interest (including but not limited to)

• Formal models of agentic behavior in LLMs
• Planning, reasoning, and memory in agent systems
• Safety, alignment, and interpretability of LLM agents
• Evaluation benchmarks and metrics for agentic performance
• Resource efficiency and deployment challenges
• Multi-agent collaboration and communication
• Human-AI collaboration
• Multi-modal and embodied LLM agents
• Tool-augmented and API-enabled agents
• Agentic applications