97 citations · 131 across the 12 of their papers we have counts for
16 papers
SIREN: Towards End-to-End Extreme-Weather Early Warning with Experience-Grounded LLM Agents
Hang Ni, Weijia Zhang, Fan Liu +2
Early warning of extreme weather is essential for mitigating the societal, economic, and environmental risks posed by hazardous weather events. However, expert-centered warning wor…
From Consistency to Complementarity: Aligned and Disentangled Multi-modal Learning for Time Series Understanding and Reasoning
Hang Ni, Weijia Zhang, Fei Wang +2
Advances in multi-modal large language models (MLLMs) have inspired time series understanding and reasoning tasks, that enable natural language querying over time series, producing…
Foundation Models for Scientific Discovery: From Paradigm Enhancement to Paradigm Transition
Fan Liu, Jindong Han, Tengfei Lyu +5
Foundation models (FMs), such as GPT-4 and AlphaFold, are reshaping the landscape of scientific research. Beyond accelerating tasks such as hypothesis generation, experimental desi…
UniExtreme: A Universal Foundation Model for Extreme Weather Forecasting
Hang Ni, Weijia Zhang, Hao Liu
Recent advancements in deep learning have led to the development of Foundation Models (FMs) for weather forecasting, yet their ability to predict extreme weather events remains lim…
Physics-Informed Teleconnection-Aware Transformer for Global Subseasonal-to-Seasonal Forecasting
Tengfei Lyu, Weijia Zhang, Hao Liu
Subseasonal-to-seasonal (S2S) forecasting, which predicts climate conditions from several weeks to months in advance, represents a critical frontier for agricultural planning, ener…
PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems
Hao Wang, Jindong Han, Wei Fan +2
Data Assimilation (DA) plays a critical role in atmospheric science by reconstructing spatially continous estimates of the system state, which serves as initial conditions for scie…
Labor Migration Modeling through Large-scale Job Query Data
Zhuoning Guo, Le Zhang, Hengshu Zhu +3
Accurate and timely modeling of labor migration is crucial for various urban governance and commercial tasks, such as local policy-making and business site selection. However, exis…
Meta-Transfer Learning Powered Temporal Graph Networks for Cross-City Real Estate Appraisal
Weijia Zhang, Jindong Han, Hao Liu +3
Real estate appraisal is important for a variety of endeavors such as real estate deals, investment analysis, and real property taxation. Recently, deep learning has shown great pr…
AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting
Tengfei Lyu, Weijia Zhang, Jinliang Deng +1
Spatio-temporal forecasting is a critical component of various smart city applications, such as transportation optimization, energy management, and socio-economic analysis. Recentl…
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
Weijia Zhang, Chenlong Yin, Hao Liu +1
Pre-trained Language Models (PLMs), such as ChatGPT, have significantly advanced the field of natural language processing. This progress has inspired a series of innovative studies…
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Weijia Zhang, Jindong Han, Zhao Xu +4
The integration of machine learning techniques has become a cornerstone in the development of intelligent urban services, significantly contributing to the enhancement of urban eff…
LLMLight: Large Language Models as Traffic Signal Control Agents
Siqi Lai, Zhao Xu, Weijia Zhang +2
Traffic Signal Control (TSC) is a crucial component in urban traffic management, aiming to optimize road network efficiency and reduce congestion. Traditional TSC methods, primaril…
Machine Learning for Urban Air Quality Analytics: A Survey
Jindong Han, Weijia Zhang, Hao Liu +1
The increasing air pollution poses an urgent global concern with far-reaching consequences, such as premature mortality and reduced crop yield, which significantly impact various a…
Chain-of-Choice Hierarchical Policy Learning for Conversational Recommendation
Wei Fan, Weijia Zhang, Weiqi Wang +2
Conversational Recommender Systems (CRS) illuminate user preferences via multi-round interactive dialogues, ultimately navigating towards precise and satisfactory recommendations.…
Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training
Fan Liu, Weijia Zhang, Hao Liu
Machine learning-based forecasting models are commonly used in Intelligent Transportation Systems (ITS) to predict traffic patterns and provide city-wide services. However, most of…
Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning
Weijia Zhang, Hao Liu, Fan Wang +4
Electric Vehicle (EV) has become a preferable choice in the modern transportation system due to its environmental and energy sustainability. However, in many large cities, EV drive…