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cs.AI2026

World of SWECraft: Agent Collaboration at Scale via Simulated Software Worlds

Shannon Zejiang Shen, Yapei Chang, Qiyao Liang +13

As teams of AI agents take on larger projects and long-standing open problems, agent collaboration offers another dimension for scaling inference-time compute. To understand what m…

cs.AI2026

Vision Language Models Cannot Reason About Physical Transformation

Dezhi Luo, Yijiang Li, Maijunxian Wang +7

Understanding physical transformations is fundamental for reasoning in dynamic environments. While Vision Language Models (VLMs) show promise in embodied applications, whether they…

cs.AI2026

SimWorld-Robotics: Synthesizing Photorealistic and Dynamic Urban Environments for Multimodal Robot Navigation and Collaboration

Yan Zhuang, Jiawei Ren, Xiaokang Ye +9

Recent advances in foundation models have shown promising results in developing generalist robotics that can perform diverse tasks in open-ended scenarios given multimodal inputs.…

cs.AI2026

SimWorld: An Open-ended Realistic Simulator for Autonomous Agents in Physical and Social Worlds

Jiawei Ren, Yan Zhuang, Xiaokang Ye +20

While LLM/VLM-powered AI agents have advanced rapidly in math, coding, and computer use, their applications in complex physical and social environments remain challenging. Building…

cs.AI2025

DeliveryBench: Can Agents Earn Profit in Real World?

Lingjun Mao, Jiawei Ren, Kun Zhou +3

LLMs and VLMs are increasingly deployed as embodied agents, yet existing benchmarks largely revolve around simple short-term tasks and struggle to capture rich realistic constraint…