3 citations · 5 across the 15 of their papers we have counts for
10 papers · 1 filter
RoboScape-R: Unified Reward-Observation World Models for Generalizable Robotics Training via RL
Yinzhou Tang, Yu Shang, Yinuo Chen +8
Achieving generalizable embodied policies remains a key challenge. Traditional policy learning paradigms, including both Imitation Learning (IL) and Reinforcement Learning (RL), st…
UrbanWorld2.0: A Multimodal Agentic Framework for Reality-Aligned 3D World Generation at City-Scale
Shengyuan Wang, Zhiheng Zheng, Yu Shang +6
The automated generation of high-fidelity, city-scale 3D environments remains a formidable challenge with profound academic and industrial implications. However, existing methods s…
LongScape: Advancing Long-Horizon Embodied World Models with Context-Aware MoE
Yu Shang, Lei Jin, Yiding Ma +4
Video-based world models hold significant potential for generating high-quality embodied manipulation data. However, current video generation methods struggle to achieve stable lon…
KeyWorld: Key Frame Reasoning Enables Effective and Efficient World Models
Sibo Li, Qianyue Hao, Yu Shang +1
Robotic world models are a promising paradigm for forecasting future environment states, yet their inference speed and the physical plausibility of generated trajectories remain cr…
MoWM: Mixture-of-World-Models for Embodied Planning via Latent-to-Pixel Feature Modulation
Yangcheng Yu, Xin Jin, Yu Shang +4
Embodied action planning is a core challenge in robotics, requiring models to generate precise actions from visual observations and language instructions. While video generation wo…
AirScape: An Aerial Generative World Model with Motion Controllability
Baining Zhao, Rongze Tang, Mingyuan Jia +9
How to enable agents to predict the outcomes of their own motion intentions in three-dimensional space has been a fundamental problem in embodied intelligence. To explore general s…
RoboScape: Physics-informed Embodied World Model
Yu Shang, Xin Zhang, Yinzhou Tang +4
World models have become indispensable tools for embodied intelligence, serving as powerful simulators capable of generating realistic robotic videos while addressing critical data…
AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems
Yu Shang, Peijie Liu, Yuwei Yan +9
The emergence of agentic recommender systems powered by Large Language Models (LLMs) represents a paradigm shift in personalized recommendations, leveraging LLMs' advanced reasonin…
AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms
Yuwei Yan, Yu Shang, Qingbin Zeng +9
The AgentSociety Challenge is the first competition in the Web Conference that aims to explore the potential of Large Language Model (LLM) agents in modeling user behavior and enha…
A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform
Yu Shang, Chen Gao, Nian Li +1
Short-video platforms show an increasing impact on people's daily lives nowadays, with billions of active users spending plenty of time each day. The interactions between users and…