For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …

Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

Large language models have shown their remarkable capabilities as a general interface for
various language-related applications. Motivated by this, we target to build a unified …

Large language models (LLMs) are currently at the forefront of intertwining AI systems with
human communication and everyday life. Due to rapid technological advances and their …

Scene simulation in autonomous driving has gained significant attention because of its huge
potential for generating customized data. However existing editable scene simulation …

Agent-based modeling and simulation have evolved as a powerful tool for modeling
complex systems, offering insights into emergent behaviors and interactions among diverse …

We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object
detection ability of multimodal large language models (MLLMs), such as GPT-4V and …

Contemporary evaluation techniques are inadequate for agentic systems. These
approaches either focus exclusively on final outcomes--ignoring the step-by-step nature of …

Various human-designed prompt engineering techniques have been proposed to improve
problem solvers based on Large Language Models (LLMs), yielding many disparate code …

Urban environments, characterized by their complex, multi-layered networks encompassing
physical, social, economic, and environmental dimensions, face significant challenges in the …