11 citations · 61 across the 61 of their papers we have counts for
65 papers
GRAM: Correcting Frozen Time-Series Foundation Models via Graph-Retrieved Amplitude Memory
Xiaoyun Yu, Xiangfei Qiu, Yonggui Huang +7
Time-series foundation models (TSFMs) enable zero-shot forecasting through large-scale cross-domain pretraining, while retrieval augmentation further improves their performance by…
WPBench: A Comprehensive Benchmark for Wind Power Forecasting
Yuhan Zhu, Jilin Hu, Xinying Cai +7
Accurate, reliable, and deployable wind power forecasting is critical for power system dispatch, renewable energy integration, and electricity market operations. Progress in this f…
MUSE: Dependency-Aware Adaptation of a Frozen Vision Backbone for Multivariate Time Series Forecasting
Xinying Cai, Junkai Lu, Yuhan Zhu +3
Multivariate time-series forecasting is essential to many real-world applications. Recent large vision models (LVMs) offer a promising paradigm by transferring cross-domain visual…
QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization
Yujie Li, Zezhi Shao, Chengqing Yu +7
Ubiquitous time series data across diverse domains enables critical applications in areas such as transportation systems and power grids. Recently, training foundation models on ma…
DGCPath: Distribution-Aware Generative Contrastive Framework for Self-supervised Path Representation Learning -- Extended Version
Sean Bin Yang, Hao Miao, Zongyi Xu +5
Due to the proliferation of vehicle trajectory data enabled by advanced sensing technologies, path representation learning has become a pivotal task in intelligent transportation s…
REFINE: Trajectory Representation Learning via Closed-Loop Transcription -- Extended Version
Sean Bin Yang, Ying Sun, Jilin Hu +5
Trajectory representation learning underpins a wide range of trajectory analytics tasks; however, most existing self-supervised approaches, whether discriminative or generative, ad…
Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework
Tianen Shen, Zhengyu Li, Yutong Li +4
Irregular multivariate time series are widely encountered in applications such as healthcare monitoring, human activity recognition, and environmental sensing. Their core challenge…
One Layer's Trash is Another Layer's Treasure: Adaptive Layer-wise Visual Token Selection in LVLMs
Yongru Chen, Kai Zhang, Zeliang Zong +4
Large Vision-Language Models (LVLMs) have achieved remarkable success across diverse multimodal tasks, yet their practical deployment remains constrained by the computational burde…
HyFAD: Hybrid Time-Frequency Diffusion with Frequency-Aware Embedding for Time Series Imputation
Hongfan Gao, Wangmeng Shen, Bin Yang +1
Diffusion models have demonstrated strong performance in time series modeling due to their ability to progressively capture complex data distributions through iterative denoising.…
Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
Xingjian Wu, Junkai Lu, Siyu Yan +4
Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existing MAS typically rely on pre…
GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables
Zhengyu Li, Xiangfei Qiu, Yuhan Zhu +4
Exogenous variables offer valuable supplementary information for predicting future endogenous variables. Forecasting with exogenous variables needs to consider both past-to-future…
DiSGMM: A Method for Time-varying Microscopic Weight Completion on Road Networks
Yan Lin, Jilin Hu, Shengnan Guo +3
Microscopic road-network weights represent fine-grained, time-varying traffic conditions obtained from individual vehicles. An example is travel speeds associated with road segment…
AMShortcut: An Inference- and Training-Efficient Inverse Design Model for Amorphous Materials
Yan Lin, Jonas A. Finkler, Tao Du +2
Amorphous materials are solids that lack long-range atomic order but possess complex short- and medium-range order. Unlike crystalline materials that can be described by unit cells…
MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models
Xiaoyun Yu, Li fan, Xiangfei Qiu +7
While Time Series Foundation Models (TSFMs) have demonstrated exceptional performance in generalized forecasting, their performance often degrades significantly when deployed in re…
ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologies
Xingjian Wu, Xvyuan Liu, Junkai Lu +6
LLM-powered Multi-Agent Systems (MAS) have emerged as an effective approach towards collaborative intelligence, and have attracted wide research interests. Among them, ``self-evolv…
SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
Xiangfei Qiu, Xvyuan Liu, Tianen Shen +4
Time series forecasting is important in many fields that require accurate predictions for decision-making. Patching techniques, commonly used and effective in time series modeling,…
Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting
Xiangfei Qiu, Kangjia Yan, Xvyuan Liu +2
Irregular multivariate time series forecasting (IMTSF) is challenging due to non-uniform sampling and variable asynchronicity. These irregularities violate the equidistant assumpti…
TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation
Xingjian Wu, Junkai Lu, Zhengyu Li +5
Time series data widely exist in real-world cyber-physical systems. Though analyzing and interpreting them contributes to significant values, e.g, disaster prediction and financial…
TimeMar: Multi-Scale Autoregressive Modeling for Unconditional Time Series Generation
Xiangyu Xu, Qingsong Zhong, Jilin Hu
Generative modeling offers a promising solution to data scarcity and privacy challenges in time series analysis. However, the structural complexity of time series, characterized by…
DiffMM: Efficient Method for Accurate Noisy and Sparse Trajectory Map Matching via One Step Diffusion
Chenxu Han, Sean Bin Yang, Jilin Hu
Map matching for sparse trajectories is a fundamental problem for many trajectory-based applications, e.g., traffic scheduling and traffic flow analysis. Existing methods for map m…
Spatial-Temporal Feedback Diffusion Guidance for Controlled Traffic Imputation
Xiaowei Mao, Huihu Ding, Yan Lin +6
Imputing missing values in spatial-temporal traffic data is essential for intelligent transportation systems. Among advanced imputation methods, score-based diffusion models have d…
FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
Xingjian Wu, Hanyin Cheng, Xiangfei Qiu +4
In this work, we introduce FLAME, a family of extremely lightweight and capable Time Series Foundation Models, which support versatile forecasting tasks via generative probabilisti…
SculptDrug : A Spatial Condition-Aware Bayesian Flow Model for Structure-based Drug Design
Qingsong Zhong, Haomin Yu, Yan Lin +3
Structure-Based drug design (SBDD) has emerged as a popular approach in drug discovery, leveraging three-dimensional protein structures to generate drug ligands. However, existing…
Spatio-Temporal Trajectory Foundation Model - Recent Advances and Future Directions
Sean Bin Yang, Ying Sun, Yunyao Cheng +3
Foundation models (FMs) have emerged as a powerful paradigm, enabling a diverse range of data analytics and knowledge discovery tasks across scientific fields. Inspired by the succ…