12 citations · 21 across the 25 of their papers we have counts for
28 papers
ClinLens: Towards Long-Horizon LLM Agents for Longitudinal Multimodal Clinical Data Science
Yuan Zhu, Ethan B. Liu, Frank Nie +3
Automating clinical data science requires agents to translate patient-centric objectives into executable workflows grounded in longitudinal multimodal evidence. Existing benchmarks…
A Cost-Effective Multimodal LLM Reasoning Framework for Question Answering over Irregular Clinical Time Series
Frank Nie, Ethan B Liu, Yuan Zhu +2
Question answering (QA) over irregular clinical time series (ICTS) plays a pivotal role in a wide range of healthcare applications. Although recent multimodal time-series large lan…
CLIR-Bench: Benchmarking Multimodal Question Answering over Irregular Clinical Time Series
Frank Nie, Ethan B. Liu, Yuan Zhu +3
Clinical time series are central to patient monitoring, risk assessment, and clinical decision support. However, they are often sparse, irregularly sampled, and asynchronous, makin…
Atmospheric Diffusion-Guided Spatio-Temporal Transformer for Nuclear Radiation Forecasting
Tengfei Lyu, Jindong Han, Hao Liu
Nuclear radiation, the energy released during atomic decay, poses persistent risks to public health and the environment, and concerns have only grown since the Fukushima accident a…
TrafficClaw: A Generalizable LLM Agent in the Unified Physical Environment for Urban Traffic Control
Siqi Lai, Pan Zhang, Yuping Zhou +3
Large language model (LLM) agents have shown strong capabilities in long-horizon reasoning, tool use, and decision-making in digital environments, yet extending them to physically…
ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis
Hao Wang, Jindong Han, Wei Fan +1
Climate research is pivotal for mitigating global environmental crises, yet the accelerating volume of multi-scale datasets and the complexity of analytical tools have created sign…
Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval
Fanpu Cao, Lu Dai, Jindong Han +1
Multivariate time series forecasting (MTSF) plays a vital role in numerous real-world applications, yet existing models remain constrained by their reliance on a limited historical…
MixTTE: Multi-Level Mixture-of-Experts for Scalable and Adaptive Travel Time Estimation
Wenzhao Jiang, Jindong Han, Ruiqian Han +1
Accurate Travel Time Estimation (TTE) is critical for ride-hailing platforms, where errors directly impact user experience and operational efficiency. While existing production sys…
DAMBench: A Multi-Modal Benchmark for Deep Learning-based Atmospheric Data Assimilation
Hao Wang, Zixuan Weng, Jindong Han +2
Data Assimilation is a cornerstone of atmospheric system modeling, tasked with reconstructing system states by integrating sparse, noisy observations with prior estimation. While t…
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…
An LLM-Powered Cooperative Framework for Large-Scale Multi-Vehicle Navigation
Yuping Zhou, Siqi Lai, Jindong Han +1
The rise of Internet of Vehicles (IoV) technologies is transforming traffic management from isolated control to a collective, multi-vehicle process. At the heart of this shift is m…
Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications
Jindong Han, Yansong Ning, Zirui Yuan +4
The long-standing vision of intelligent cities is to create efficient, livable, and sustainable urban environments using big data and artificial intelligence technologies. Recently…
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…
Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph Learning
Hang Ni, Jindong Han, Nengjun Zhu +1
Graph Anomaly Detection (GAD) plays a vital role in various data mining applications such as e-commerce fraud prevention and malicious user detection. Recently, Graph Neural Networ…
NRFormer: Nationwide Nuclear Radiation Forecasting with Spatio-Temporal Transformer
Tengfei Lyu, Jindong Han, Hao Liu
Nuclear radiation, which refers to the energy emitted from atomic nuclei during decay, poses significant risks to human health and environmental safety. Recently, advancements in m…
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…
Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction
Ziyang Wu, Fan Liu, Jindong Han +2
As various types of crime continue to threaten public safety and economic development, predicting the occurrence of multiple types of crimes becomes increasingly vital for effectiv…
Erase then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning
Zhe-Rui Yang, Jindong Han, Chang-Dong Wang +1
Graph unlearning, which aims to eliminate the influence of specific nodes, edges, or attributes from a trained Graph Neural Network (GNN), is essential in applications where privac…
GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning
Zhe-Rui Yang, Jindong Han, Chang-Dong Wang +1
Graph Neural Networks (GNNs) have demonstrated remarkable proficiency in handling a range of graph analytical tasks across various domains, such as e-commerce and social networks.…
RePST: Language Model Empowered Spatio-Temporal Forecasting via Semantic-Oriented Reprogramming
Hao Wang, Jindong Han, Wei Fan +2
Spatio-temporal forecasting is pivotal in numerous real-world applications, including transportation planning, energy management, and climate monitoring. In this work, we aim to ha…
SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting
Zixuan Weng, Jindong Han, Wenzhao Jiang +1
In recent years, advancements in deep learning have spurred the development of numerous models for Long-term Time Series Forecasting (LTSF). However, most existing approaches strug…
Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
Wenzhao Jiang, Jindong Han, Hao Liu +3
Rapid urbanization has significantly escalated traffic congestion, underscoring the need for advanced congestion prediction services to bolster intelligent transportation systems.…
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…
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…