6 papers
Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos
Jinzhou Tang, Zijun Zhang, Jing Yang +10
Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manual environment construction…
Causally Debiased Latent Action Model for Embodied Action-Conditioned World Models
Yufan Wei, Kun Zhou, Lingjun Mao +9
Action-conditioned world models (ACWMs) aim to simulate future observations conditioned on embodied actions. However, learning controllable ACWMs requires large-scale action-labele…
AgentSpec: Understanding Embodied Agent Scaffolds Through Controlled Composition
Jixuan Chen, Jianzhi Shen, Haoqiang Kang +10
LLM agents are increasingly built not as single model calls, but as scaffolded systems that combine reasoning, memory, reflection, action execution, and learning. While such scaffo…
SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning
Haoqiang Kang, Xiaokang Ye, Yuhan Liu +5
LLM/VLM-based digital agents have advanced rapidly thanks to scalable sandboxes for coding, web navigation, and computer use, which provide rich interactive training grounds. In co…
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…
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…