64 citations · 65 across the 16 of their papers we have counts for
16 papers
Robo-ValueRL: Reliable Value Estimation for Offline-to-Online Reinforcement Learning
Wenke Xia, Pei Ren, Wenbo Yu +10
Offline-to-online reinforcement learning is promising for generalizable robotic manipulation, yet its full-stack complexity obscures reproduction and diagnosis. Within such systems…
NeuroCogMap Reveals Cognitive Organization of Large Language Models
Zhongxiang Sun, Haolang Lu, Qiang Ma +11
Understanding how complex cognitive functions are organized within artificial systems is central to interpreting large language models (LLMs) and relating them to biological cognit…
Toward Autonomous Long-Horizon Engineering for ML Research
Guoxin Chen, Jie Chen, Lei Chen +7
Agentic systems increasingly automate pieces of AI research. Yet turning underspecified research objectives into runnable, experimentally validated ML systems remains a central bot…
Towards Long-horizon Agentic Multimodal Search
Yifan Du, Zikang Liu, Jinbiao Peng +5
Multimodal deep search agents have shown great potential in solving complex tasks by iteratively collecting textual and visual evidence. However, managing the heterogeneous informa…
Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
Guanting Dong, Junting Lu, Junjie Huang +17
Large language models are increasingly expected to serve as general-purpose agents that interact with external, stateful tool environments. The Model Context Protocol (MCP) and bro…
Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration
Zhipeng Chen, Tao Qian, Wayne Xin Zhao +1
Recently, scaling reinforcement learning with verifiable rewards (RLVR) for large language models (LLMs) has emerged as an effective training paradigm for significantly improving m…
Leveraging LLM-based agents for social science research: insights from citation network simulations
Jiarui Ji, Runlin Lei, Xuchen Pan +8
The emergence of Large Language Models (LLMs) demonstrates their potential to encapsulate the logic and patterns inherent in human behavior simulation by leveraging extensive web d…
L2V-CoT: Cross-Modal Transfer of Chain-of-Thought Reasoning via Latent Intervention
Yuliang Zhan, Xinyu Tang, Han Wan +3
Recently, Chain-of-Thought (CoT) reasoning has significantly enhanced the capabilities of large language models (LLMs), but Vision-Language Models (VLMs) still struggle with multi-…
Nowcast3D: Reliable precipitation nowcasting via gray-box learning
Huaguan Chen, Wei Han, Haofei Sun +9
Reliable nowcasting of extreme precipitation remains difficult because convective systems are strongly nonlinear, multiscale, and nonstationary in 3D. Radar is the backbone of nowc…
Benchmarking LLMs' Swarm intelligence
Kai Ruan, Mowen Huang, Ji-Rong Wen +1
Large Language Models (LLMs) show potential for complex reasoning, yet their capacity for emergent coordination in Multi-Agent Systems (MAS) when operating under strict swarm-like…
FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis
Luxi Chen, Zihan Zhou, Min Zhao +6
Generating flexible-view 3D scenes, including 360° rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel fr…
MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation
Qi Wang, Yuan Mi, Haoyun Wang +5
Solving partial differential equations (PDEs) by numerical methods meet computational cost challenge for getting the accurate solution since fine grids and small time steps are req…
Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
Yuan Mi, Pu Ren, Hongteng Xu +6
Data-centric methods have shown great potential in understanding and predicting spatiotemporal dynamics, enabling better design and control of the object system. However, deep lear…
PCNet: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics
Qi Wang, Pu Ren, Hao Zhou +10
When solving partial differential equations (PDEs), classical numerical methods often require fine mesh grids and small time stepping to meet stability, consistency, and convergenc…
Discovering physical laws with parallel symbolic enumeration
Kai Ruan, Yilong Xu, Ze-Feng Gao +4
Symbolic regression plays a crucial role in modern scientific research thanks to its capability of discovering concise and interpretable mathematical expressions from data. A key c…
AI-accelerated Discovery of Altermagnetic Materials
Ze-Feng Gao, Shuai Qu, Bocheng Zeng +5
Altermagnetism, a new magnetic phase, has been theoretically proposed and experimentally verified to be distinct from ferromagnetism and antiferromagnetism. Although altermagnets h…