3 papers
cs.RO2026
Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART)
Jingtian Yan, Zhifei Li, William Kang +7
We present Scalable Multi-Agent Realistic Testbed (SMART), a realistic and efficient software tool for evaluating Multi-Agent Path Finding (MAPF) algorithms. MAPF focuses on planni…
cs.CL2026
CocoaBench: Evaluating Unified Digital Agents in the Wild
CocoaBench Team, Shibo Hao, Zhining Zhang +29
LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds and models are increasingly int…
cs.AI2026
Analyzing Planner Design Trade-offs for MAPF under ADG-based Realistic Execution
Jingtian Yan, Zhifei Li, William Kang +2
Multi-Agent Path Finding (MAPF) algorithms are increasingly deployed in industrial warehouses and automated manufacturing facilities, where robots must operate reliably under real-…