activity
20192026
most citedA Survey on Vision-Language-Action Models for Embodied AI

29 citations · 70 across the 33 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

ProWorld: Progress-Aware Hyperbolic World Models for Long-Horizon Visual Goal Reaching

Zihan Liu, Yuzhe Zhuang, Yuanzu Li +4

JEPA-style visual world models offer an effective paradigm for visual goal planning by predicting future latent representations. Existing methods typically learn local transition c…

cs.AI2025

MineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agents

Ziming Wei, Bingqian Lin, Zijian Jiao +5

Spatial Planning is a crucial part in the field of spatial intelligence, which requires the understanding and planning about object arrangements in space perspective. AI agents wit…

cs.AI2022

Planning Immediate Landmarks of Targets for Model-Free Skill Transfer across Agents

Minghuan Liu, Zhengbang Zhu, Menghui Zhu +3

In reinforcement learning applications like robotics, agents usually need to deal with various input/output features when specified with different state/action spaces by their deve…

cs.AI2022★ 4 cited

RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow

Zhengbang Zhu, Shenyu Zhang, Yuzheng Zhuang +11

High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating tr…

cs.AI2021★ 8 cited

Learning Symbolic Rules for Interpretable Deep Reinforcement Learning

Zhihao Ma, Yuzheng Zhuang, Paul Weng +4

Recent progress in deep reinforcement learning (DRL) can be largely attributed to the use of neural networks. However, this black-box approach fails to explain the learned policy i…