1 citations · 2 across the 27 of their papers we have counts for
32 papers
Self-Evolving Agents as Dynamic Graph Transformation: A Survey and New Perspective
Yuanyuan Xu, Wenjie Zhang, Yin Chen +2
Large language model (LLM)-based agents are increasingly becoming self-evolving systems that persist across interactions, maintain memories, use tools, acquire skills, refine workf…
Algebraic Subgraph Counting
Qiuyu Guo, Jianye Yang, Wenjie Zhang +3
Subgraph isomorphism counting is a fundamental problem in graph analytics, which aims to find the number of subgraph isomorphisms of a query graph in a data graph. The candidate tr…
Efficient Approximate Nearest Neighbor Search under Multi-Attribute Range Filter
Yuanhang Yu, Dawei Cheng, Ying Zhang +3
Nearest neighbor search on high-dimensional vectors is fundamental in modern AI and database systems. In many real-world applications, queries involve constraints on multiple numer…
HyperJoin: LLM-augmented Hypergraph Link Prediction for Joinable Table Discovery
Shiyuan Liu, Jianwei Wang, Xuemin Lin +3
As a pivotal task in data lake management, joinable table discovery has attracted widespread interest. While existing language model-based methods achieve remarkable performance by…
FADTI: Fourier and Attention Driven Diffusion for Multivariate Time Series Imputation
Runze Li, Hanchen Wang, Wenjie Zhang +4
Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sensor failures and irregular sampling le…
DHG-Bench: A Comprehensive Benchmark for Deep Hypergraph Learning
Fan Li, Xiaoyang Wang, Wenjie Zhang +2
Deep graph models have achieved great success in network representation learning. However, their focus on pairwise relationships restricts their ability to learn pervasive higher-o…
Triangle Counting in Hypergraph Streams: A Complete and Practical Approach
Lingkai Meng, Long Yuan, Xuemin Lin +2
Triangle counting in hypergraph streams, including both hyper-vertex and hyper-edge triangles, is a fundamental problem in hypergraph analytics, with broad applications. However, e…
Accelerating Historical K-Core Search in Temporal Graphs
Zhuo Ma, Dong Wen, Kaiyu Chen +3
We study the temporal k-core component search (TCCS), which outputs the k-core containing the query vertex in the snapshot over an arbitrary query time window in a temporal graph.…
Accelerating K-Core Computation in Temporal Graphs
Zhuo Ma, Dong Wen, Hanchen Wang +3
We address the problem of enumerating all temporal k-cores given a query time range and a temporal graph, which suffers from poor efficiency and scalability in the state-of-the-art…
Empowering Tabular Data Preparation with Language Models: Why and How?
Mengshi Chen, Yuxiang Sun, Tengchao Li +5
Data preparation is a critical step in enhancing the usability of tabular data and thus boosts downstream data-driven tasks. Traditional methods often face challenges in capturing…
HiTeC: Hierarchical Contrastive Learning on Text-Attributed Hypergraph with Semantic-Aware Augmentation
Mengting Pan, Fan Li, Chen Chen +2
Contrastive learning (CL) has become a dominant paradigm for self-supervised hypergraph learning, enabling effective training without costly labels. However, node entities in real-…
Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN
Wei Huang, Hanchen Wang, Dong Wen +3
Graph Edit Distance (GED) is a fundamental graph similarity metric widely used in various applications. However, computing GED is an NP-hard problem. Recent state-of-the-art hybrid…
Efficient Computation of Hyper-triangles on Hypergraphs
Haozhe Yin, Kai Wang, Wenjie Zhang +3
Hypergraphs, which use hyperedges to capture groupwise interactions among different entities, have gained increasing attention recently for their versatility in effectively modelin…
Motif Counting in Complex Networks: A Comprehensive Survey
Haozhe Yin, Kai Wang, Wenjie Zhang +3
Motif counting plays a crucial role in understanding the structural properties of networks. By computing motif frequencies, researchers can draw key insights into the structural pr…
DiffGED: Computing Graph Edit Distance via Diffusion-based Graph Matching
Wei Huang, Hanchen Wang, Dong Wen +3
The Graph Edit Distance (GED) problem, which aims to compute the minimum number of edit operations required to transform one graph into another, is a fundamental challenge in graph…
ProbDiffFlow: An Efficient Learning-Free Framework for Probabilistic Single-Image Optical Flow Estimation
Mo Zhou, Jianwei Wang, Xuanmeng Zhang +5
This paper studies optical flow estimation, a critical task in motion analysis with applications in autonomous navigation, action recognition, and film production. Traditional opti…
UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs
Yuanyuan Xu, Wenjie Zhang, Xuemin Lin +1
Dynamic graphs are formulated in continuous-time or discrete-time dynamic graphs. They differ in temporal granularity: Continuous-Time Dynamic Graphs (CTDGs) exhibit rapid, localiz…
Unlocking Multi-Modal Potentials for Link Prediction on Dynamic Text-Attributed Graphs
Yuanyuan Xu, Wenjie Zhang, Ying Zhang +2
Dynamic Text-Attributed Graphs (DyTAGs) are a novel graph paradigm that captures evolving temporal events (edges) alongside rich textual attributes. Existing studies can be broadly…
Ensemble-based Deep Multilayer Community Search
Jianwei Wang, Yuehai Wang, Kai Wang +3
Multilayer graphs, consisting of multiple interconnected layers, are widely used to model diverse relationships in the real world. A community is a cohesive subgraph that offers va…
On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing
Jianwei Wang, Kai Wang, Ying Zhang +3
Missing data imputation, which aims to impute the missing values in the raw datasets to achieve the completeness of datasets, is crucial for modern data-driven models like large la…
Efficient Dynamic Attributed Graph Generation
Fan Li, Xiaoyang Wang, Dawei Cheng +3
Data generation is a fundamental research problem in data management due to its diverse use cases, ranging from testing database engines to data-specific applications. However, rea…
Counting Butterflies over Streaming Bipartite Graphs with Duplicate Edges
Lingkai Meng, Long Yuan, Xuemin Lin +3
Bipartite graphs are commonly used to model relationships between two distinct entities in real-world applications, such as user-product interactions, user-movie ratings and collab…
TCGU: Data-centric Graph Unlearning based on Transferable Condensation
Fan Li, Xiaoyang Wang, Dawei Cheng +3
With growing demands for data privacy and model robustness, graph unlearning (GU), which erases the influence of specific data on trained GNN models, has gained significant attenti…
Efficient Maximal Frequent Group Enumeration in Temporal Bipartite Graphs
Yanping Wu, Renjie Sun, Xiaoyang Wang +4
Cohesive subgraph mining is a fundamental problem in bipartite graph analysis. In reality, relationships between two types of entities often occur at some specific timestamps, whic…