Publications (35)
Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models
Yu Shang, Yu Li, Fengli Xu +1
Large language models (LLMs) have shown impressive emergent abilities in a wide range of tasks, but the associated expensive API cost greatly limits the real application. Previous…
WorldArena: A Unified Benchmark for Evaluating Perception and Functional Utility of Embodied World Models
Yu Shang, Zhuohang Li, Yiding Ma +18
While world models have emerged as a cornerstone of embodied intelligence by enabling agents to reason about environmental dynamics through action-conditioned prediction, their eva…
Distributed Quantum Neural Networks on Distributed Photonic Quantum Computing
Kuan-Cheng Chen, Chen-Yu Liu, Yu Shang +2
We introduce a distributed quantum-classical framework that synergizes photonic quantum neural networks (QNNs) with matrix-product-state (MPS) mapping to achieve parameter-efficien…
Towards Biologically Plausible Computing: A Comprehensive Comparison
Changze Lv, Yufei Gu, Zhengkang Guo +16
Backpropagation is a cornerstone algorithm in training neural networks for supervised learning, which uses a gradient descent method to update network weights by minimizing the dis…
UrbanWorld: An Urban World Model for 3D City Generation
Yu Shang, Yuming Lin, Yu Zheng +6
Cities, as the essential environment of human life, encompass diverse physical elements such as buildings, roads and vegetation, which continuously interact with dynamic entities l…
On Newman-Penrose constants of stationary space-times
Xiaoning Wu, Yu Shang
We consider the general asymptotic expression of stationary space-time. Using Killing equation, we reduce the dynamical freedom of Einstein equation to the in-going gravitational w…
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…
RNG: Reducing Multi-level Noise and Multi-grained Semantic Gap for Joint Multimodal Aspect-Sentiment Analysis
Yaxin Liu, Yan Zhou, Ziming Li +4
As an important multimodal sentiment analysis task, Joint Multimodal Aspect-Sentiment Analysis (JMASA), aiming to jointly extract aspect terms and their associated sentiment polari…
Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network
Zhenyu Han, Fengli Xu, Jinghan Shi +4
In the past decade, the heterogeneous information network (HIN) has become an important methodology for modern recommender systems. To fully leverage its power, manually designed n…
Understanding World or Predicting Future? A Comprehensive Survey of World Models
Jingtao Ding, Yunke Zhang, Yu Shang +12
The concept of world models has garnered significant attention due to advancements in multimodal large language models such as GPT-4 and video generation models such as Sora, which…
Stoichiometric cluster learning for few-shot property prediction of multi-ionic integrated energetic materials
Ming-Yu Guo, Wei-Jia Zou, Yu Shang +1
Multi-ionic materials pose a distinct representational challenge in machine learning-driven materials design. Different from single-molecule or composition-based materials, their p…
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…
AgentSquare: Automatic LLM Agent Search in Modular Design Space
Yu Shang, Yu Li, Keyu Zhao +4
Recent advancements in Large Language Models (LLMs) have led to a rapid growth of agentic systems capable of handling a wide range of complex tasks. However, current research large…
The search for black hole binaries using a genetic algorithm
Antoine Petiteau, Yu Shang, Stanislav Babak
In this work we use genetic algorithm to search for the gravitational wave signal from the inspiralling massive Black Hole binaries in the simulated LISA data. We consider a single…
EMRI data analysis with a phenomenological waveform
Yan Wang, Yu Shang, Stanislav Babak
Extreme mass ratio inspirals (EMRIs) (capture and inspiral of a compact stellar mass object into a Massive Black Hole (MBH)) are among the most interesting objects for the gravitat…
Kaleidoscopic Background Attack: Disrupting Pose Estimation with Multi-Fold Radial Symmetry Textures
Xinlong Ding, Hongwei Yu, Jiawei Li +5
Camera pose estimation is a fundamental computer vision task that is essential for applications like visual localization and multi-view stereo reconstruction. In the object-centric…
Aerial World Model for Long-horizon Visual Generation and Navigation in 3D Space
Weichen Zhang, Peizhi Tang, Xin Zeng +12
Unmanned aerial vehicles (UAVs) have emerged as powerful embodied agents. One of the core abilities is autonomous navigation in large-scale three-dimensional environments. Existing…
Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control
Jianjie Fang, Yongyan Xu, Ziyou Wang +13
World models are rapidly becoming a core infrastructure for embodied intelligence and interactive agents: they provide controllable simulators in which agents can perceive, act, fo…
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…
Light Cone Structure near Null Infinity of the Kerr Metric
Shan Bai, Zhoujian Cao, Xuefei Gong +3
Motivated by our attempt to understand the question of angular momentum of a relativistic rotating source carried away by gravitational waves, in the asymptotic regime near future…
RAISECity: A Multimodal Agent Framework for Reality-Aligned 3D World Generation at City-Scale
Shengyuan Wang, Zhiheng Zheng, Yu Shang +6
City-scale 3D generation is of great importance for the development of embodied intelligence and world models. Existing methods, however, face significant challenges regarding qual…
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…
Nitrogen-Vacancy Engineering for Controlled Phase Transitions in CrN(111) Epitaxial Films
XiaoXu Zhang, Yang Li, Yu Shang +6
The phase transition in CrN epitaxial films is substantially suppressed by epitaxial constraint. Here, we propose that nitrogen (N) vacancies can be taken as a knob to regulate the…
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…
The search for spinning black hole binaries in mock LISA data using a genetic algorithm
Antoine Petiteau, Yu Shang, Stanislav Babak +1
Coalescing massive Black Hole binaries are the strongest and probably the most important gravitational wave sources in the LISA band. The spin and orbital precessions bring complex…
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…
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
Yu Shang, Yinzhou Tang, Yiding Ma +22
World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…
The Mock LISA Data Challenges: from Challenge 3 to Challenge 4
Stanislav Babak, John G. Baker, Matthew J. Benacquista +27
The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of one or more data…
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…
The Mock LISA Data Challenges: from Challenge 1B to Challenge 3
Stanislav Babak, John G. Baker, Matthew J. Benacquista +27
The Mock LISA Data Challenges are a programme to demonstrate and encourage the development of LISA data-analysis capabilities, tools and techniques. At the time of this workshop, t…
Perceiving exposure segregation with open urban imagery
Yunke Zhang, Ruolong Ma, Xin Zhang +4
Socioeconomic exposure segregation -- the lack of daily interaction between income groups -- erodes social capital and entrenches inequality, yet the specific physical features tha…
WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation
Baining Zhao, Jiacheng Xu, Weicheng Feng +13
Aerial vision-language navigation (VLN) requires agents to follow natural-language instructions through closed-loop perception and action in 3D environments. We argue that aerial V…
Dreaming when Necessary: Advancing World Action Models with Adaptive Multi-Modal Reasoning
Yinzhou Tang, Jingbo Xu, Yu Shang +4
World Action Models (WAMs) offer a promising approach to embodied intelligence, yet existing methods rely heavily on video prediction as action priors and lack adaptive multimodal…
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…
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…