1 citations · 3 across the 13 of their papers we have counts for
14 papers
ProfiLLM: Utility-Aligned Agentic User Profiling for Industrial Ride-Hailing Dispatch
Tengfei Lyu, Zirui Yuan, Xu Liu +4
Bringing Large Language Models (LLMs) into industrial ride-hailing dispatch as semantic feature extractors over platform-scale behavioral logs is a compelling but under-explored da…
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…
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…
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…
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…
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…
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…