PPaperPicks

Di Jin

Tianjin University, College of Intelligence and Computing, China

39 papers at tracked venues · 27 at CORE A* · active 2024–2026

DBLP profile ↗ORCID 0000-0002-7445-9936 ↗Homepage ↗

Venues

AAAI ×13IJCAI ×12NeurIPS ×6WWW ×6ICML ×2

Frequent coauthors

Dongxiao He
×29
Xiaobao Wang
×16
Zhizhi Yu
×10
Zhen Wang
×10
Bingdao Feng
×7
Liang Yang
×6
Jianguo Wei
×5
Fengyu Yan
×4
Cuiying Huo
×4
Jitao Zhao
×4
Zhiyong Feng
×4
Jiaming Zhuo
×4

Papers

  1. ARNS: Adaptive Relation-Aware Negative Sampling with Curriculum Learning for Inductive Knowledge Graph Completion
    AAAI 2026 ·
    Ling Ding
    ,
    Zhizhi Yu
    , Di Jin,
    Lei Huang
  2. Cross-Type Semantic Alignment for Multi-Type Anomaly Detection in Heterogeneous Graphs
    WWW 2026 · Di Jin,
    Xiao Huang
    ,
    Xiaobao Wang
    ,
    Fengyu Yan
    ,
    Luzhi Wang
    ,
    Hongxiang Liang
  3. DuoKD: Dual Knowledge Distillation from Large Language Models for Robust Graph Neural Networks
    AAAI 2026 ·
    Cuiying Huo
    ,
    Xiaotong Huang
    ,
    Dongxiao He
    ,
    Yixuan Du
    ,
    Wenhuan Lu
    , Di Jin
  4. IVQ-GNN: Mitigating Performance Gap from Graph Connection Pattern Inconsistency via Vector Quantization
    WWW 2026 · Di Jin,
    Yixuan Du
    ,
    Cuiying Huo
    ,
    Xiaotong Huang
    ,
    Ruqiong Zhang
    ,
    Xiaobao Wang
    ,
    Yawen Li
  5. Integrated Mixture of Neighborhood and Community Experts for Graph-Based Fraud Detection
    WWW 2026 ·
    Zhizhi Yu
    , Di Jin,
    Dongxiao He
    ,
    Wenhuan Lu
    ,
    Jianguo Wei
  6. Mitigating Noise and Imbalance in Social Governance Graphs for Multi-Type Risk Assessment
    AAAI 2026 · Di Jin,
    Haotian Zhao
    ,
    Xiaobao Wang
    ,
    Fengyu Yan
    ,
    Dongxiao He
  7. Structure-Enhanced Adapter for Self-Supervised Heterogeneous Graph Learning
    AAAI 2026 ·
    Fengyu Yan
    , Di Jin,
    Xiaobao Wang
    ,
    Qianhua Tang
    ,
    Dongxiao He
  8. Towards Graph Foundation Model: Node Feature Transfer Invariant Modeling on General Graphs
    WWW 2026 ·
    Jitao Zhao
    ,
    Yi Wang
    ,
    Yawen Li
    ,
    Dongxiao He
    , Di Jin,
    Zhiyong Feng
    ,
    Weixiong Zhang
  9. Unveiling Backdoor Propagation in Graphs: Neuron-Centric Defense Mechanisms
    WWW 2026 · Di Jin,
    Bingdao Feng
    ,
    Xiaobao Wang
    ,
    Yuxiang Zhang
    ,
    Zechuan Zhang
    ,
    Liang Yang
    ,
    Dongxiao He
    ,
    Zhen Wang
  10. A Closer Look at Graph Transformers: Cross-Aggregation and Beyond
    NeurIPS 2025 ·
    Jiaming Zhuo
    ,
    Ziyi Ma
    ,
    Yintong Lu
    ,
    Yuwei Liu
    ,
    Kun Fu
    , Di Jin,
    Chuan Wang
    ,
    Wenning Wu
    ,
    Zhen Wang
    ,
    Xiaochun Cao
    ,
    Liang Yang
  11. A Dynamic Knowledge Update-Driven Model with Large Language Models for Fake News Detection
    IJCAI 2025 · Di Jin,
    Jun Yang
    ,
    Xiaobao Wang
    ,
    Junwei Zhang
    ,
    Shuqi Li
    ,
    Dongxiao He
  12. A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities
    IJCAI 2025 ·
    Pengfei Jiao
    ,
    Hongjiang Chen
    ,
    Xuan Guo
    ,
    Zhidong Zhao
    ,
    Dongxiao He
    , Di Jin
  13. Attribute Association Driven Multi-Task Learning for Session-based Recommendation
    IJCAI 2025 ·
    Xinyao Wang
    ,
    Zhizhi Yu
    ,
    Dongxiao He
    ,
    Liang Yang
    ,
    Jianguo Wei
    , Di Jin
  14. Backdoor Attack on Propagation-based Rumor Detectors
    AAAI 2025 · Di Jin,
    Yujun Zhang
    ,
    Bingdao Feng
    ,
    Xiaobao Wang
    ,
    Dongxiao He
    ,
    Zhen Wang
  15. Disentangled Graph Spectral Domain Adaptation
    ICML 2025 ·
    Liang Yang
    ,
    Xin Chen
    ,
    Jiaming Zhuo
    , Di Jin,
    Chuan Wang
    ,
    Xiaochun Cao
    ,
    Zhen Wang
    ,
    Yuanfang Guo
  16. Do We Really Need Message Passing in Brain Network Modeling?
    ICML 2025 ·
    Liang Yang
    ,
    Yuwei Liu
    ,
    Jiaming Zhuo
    , Di Jin,
    Chuan Wang
    ,
    Zhen Wang
    ,
    Xiaochun Cao
  17. Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling
    AAAI 2025 ·
    Yongqi Huang
    ,
    Jitao Zhao
    ,
    Dongxiao He
    , Di Jin,
    Yuxiao Huang
    ,
    Zhen Wang
  18. Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection
    AAAI 2025 ·
    Zhizhi Yu
    ,
    Chundong Liang
    ,
    Xinglong Chang
    ,
    Dongxiao He
    , Di Jin,
    Jianguo Wei
  19. Exploiting Self-Refining Normal Graph Structures for Robust Defense against Unsupervised Adversarial Attacks
    IJCAI 2025 ·
    Bingdao Feng
    , Di Jin,
    Xiaobao Wang
    ,
    Dongxiao He
    ,
    Jingyi Cao
    ,
    Zhen Wang
  20. Feature-Structure Adaptive Completion Graph Neural Network for Cold-start Recommendation
    AAAI 2025 ·
    Songyuan Lei
    ,
    Xinglong Chang
    ,
    Zhizhi Yu
    ,
    Dongxiao He
    ,
    Cuiying Huo
    ,
    Jianrong Wang
    , Di Jin
  21. HGMP: Heterogeneous Graph Multi-Task Prompt Learning
    IJCAI 2025 ·
    Pengfei Jiao
    ,
    Jialong Ni
    , Di Jin,
    Xuan Guo
    ,
    Huan Liu
    ,
    Hongjiang Chen
    ,
    Yanxian Bi
  22. HeterGP: Bridging Heterogeneity in Graph Neural Networks with Multi-View Prompting
    AAAI 2025 ·
    Fengyu Yan
    ,
    Xiaobao Wang
    ,
    Dongxiao He
    ,
    Longbiao Wang
    ,
    Jianwu Dang
    , Di Jin
  23. Heterogeneous Temporal Hypergraph Neural Network
    IJCAI 2025 ·
    Huan Liu
    ,
    Pengfei Jiao
    ,
    Mengzhou Gao
    ,
    Chaochao Chen
    , Di Jin
  24. Integrating Co-Training with Edge Discrimination to Enhance Graph Neural Networks Under Heterophily
    AAAI 2025 ·
    Siqi Liu
    ,
    Dongxiao He
    ,
    Zhizhi Yu
    , Di Jin,
    Zhiyong Feng
    ,
    Weixiong Zhang
  25. LLGformer: Learnable Long-range Graph Transformer for Traffic Flow Prediction
    WWW 2025 · Di Jin,
    Cuiying Huo
    ,
    Jiayi Shi
    ,
    Dongxiao He
    ,
    Jianguo Wei
    ,
    Philip S. Yu
  26. LoSplit: Loss-Guided Dynamic Split for Training-Time Defense Against Graph Backdoor Attacks
    NeurIPS 2025 · Di Jin,
    Yuxiang Zhang
    ,
    Bingdao Feng
    ,
    Xiaobao Wang
    ,
    Dongxiao He
    ,
    Zhen Wang
  27. One Prompt Fits All: Universal Graph Adaptation for Pretrained Models
    NeurIPS 2025 ·
    Yongqi Huang
    ,
    Jitao Zhao
    ,
    Dongxiao He
    ,
    Xiaobao Wang
    ,
    Yawen Li
    ,
    Yuxiao Huang
    , Di Jin,
    Zhiyong Feng
  28. Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective
    IJCAI 2025 · Di Jin,
    Jingyi Cao
    ,
    Xiaobao Wang
    ,
    Bingdao Feng
    ,
    Dongxiao He
    ,
    Longbiao Wang
    ,
    Jianwu Dang
  29. Single-Node Trigger Backdoor Attacks in Graph-Based Recommendation Systems
    IJCAI 2025 ·
    Runze Li
    , Di Jin,
    Xiaobao Wang
    ,
    Dongxiao He
    ,
    Bingdao Feng
    ,
    Zhen Wang
  30. Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
    NeurIPS 2025 ·
    Xiaobao Wang
    ,
    Ruoxiao Sun
    ,
    Yujun Zhang
    ,
    Bingdao Feng
    ,
    Dongxiao He
    ,
    Luzhi Wang
    , Di Jin
  31. Towards Global-Topology Relation Graph for Inductive Knowledge Graph Completion
    AAAI 2025 ·
    Ling Ding
    ,
    Lei Huang
    ,
    Zhizhi Yu
    , Di Jin,
    Dongxiao He
  32. Universal Graph Self-Contrastive Learning
    IJCAI 2025 ·
    Liang Yang
    ,
    Yukun Cai
    ,
    Hui Ning
    ,
    Jiaming Zhuo
    , Di Jin,
    Ziyi Ma
    ,
    Yuanfang Guo
    ,
    Chuan Wang
    ,
    Zhen Wang
  33. Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module
    NeurIPS 2024 ·
    Jingbo Zhou
    ,
    Yixuan Du
    ,
    Ruqiong Zhang
    ,
    Jun Xia
    ,
    Zhizhi Yu
    ,
    Zelin Zang
    , Di Jin,
    Carl Yang
    ,
    Rui Zhang
    ,
    Stan Z. Li
  34. FUG: Feature-Universal Graph Contrastive Pre-training for Graphs with Diverse Node Features
    NeurIPS 2024 ·
    Jitao Zhao
    , Di Jin,
    Meng Ge
    ,
    Lianze Shan
    ,
    Xin Wang
    ,
    Dongxiao He
    ,
    Zhiyong Feng
  35. GOODAT: Towards Test-Time Graph Out-of-Distribution Detection
    AAAI 2024 ·
    Luzhi Wang
    ,
    Dongxiao He
    ,
    He Zhang
    ,
    Yixin Liu
    ,
    Wenjie Wang
    ,
    Shirui Pan
    , Di Jin,
    Tat-Seng Chua
  36. Generalized Taxonomy-Guided Graph Neural Networks
    IJCAI 2024 ·
    Yu Zhou
    , Di Jin,
    Jianguo Wei
    ,
    Dongxiao He
    ,
    Zhizhi Yu
    ,
    Weixiong Zhang
  37. Joint Domain Adaptive Graph Convolutional Network
    IJCAI 2024 ·
    Niya Yang
    ,
    Ye Wang
    ,
    Zhizhi Yu
    ,
    Dongxiao He
    ,
    Xin Huang
    , Di Jin
  38. Multi-Modal Sarcasm Detection Based on Dual Generative Processes
    IJCAI 2024 ·
    Huiying Ma
    ,
    Dongxiao He
    ,
    Xiaobao Wang
    , Di Jin,
    Meng Ge
    ,
    Longbiao Wang
  39. Unveiling Implicit Deceptive Patterns in Multi-Modal Fake News via Neuro-Symbolic Reasoning
    AAAI 2024 ·
    Yiqi Dong
    ,
    Dongxiao He
    ,
    Xiaobao Wang
    ,
    Youzhu Jin
    ,
    Meng Ge
    ,
    Carl Yang
    , Di Jin