Truth Inference in Crowdsourcing: Is the Problem Solved? - Yudian Zheng; Guoliang Li 001; Yuanbing Li; Caihua Shan; Reynold Cheng (Proc. VLDB Endow., 2017)

T-Crowd: Effective Crowdsourcing for Tabular Data. - Caihua Shan; Nikos Mamoulis; Guoliang Li 001; Reynold Cheng; Zhipeng Huang 001; Yudian Zheng (ICDE, 2018)

A Toolkit for Managing Multiple Crowdsourced Top-K Queries. - Caihua Shan; Leong Hou U; Nikos Mamoulis; Reynold Cheng (CIKM, 2020)

A General Early-Stopping Module for Crowdsourced Ranking. - Caihua Shan; Leong Hou U; Nikos Mamoulis; Reynold Cheng; Xiang Li 067 (DASFAA (2), 2020)

An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms. - Caihua Shan; Nikos Mamoulis; Reynold Cheng; Guoliang Li 001; Xiang Li 067; Yuqiu Qian (ICDE, 2020)

CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data. - Xiang Li 067; Ben Kao; Caihua Shan; Dawei Yin; Martin Ester (KDD, 2020)

A Crowdsourcing Framework for Collecting Tabular Data. - Caihua Shan; Nikos Mamoulis; Guoliang Li 001; Reynold Cheng; Zhipeng Huang 001; Yudian Zheng (IEEE Trans. Knowl. Data Eng., 2020)

How Powerful is Graph Convolution for Recommendation? - Yifei Shen; Yongji Wu; Yao Zhang 009; Caihua Shan; Jun Zhang 004; Khaled B. Letaief; Dongsheng Li 002 (CIKM, 2021)

CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph. - Yao Zhang 009; Yun Xiong; Dongsheng Li 002; Caihua Shan; Kan Ren; Yangyong Zhu (CIKM, 2021)

Recognizing Vector Graphics without Rasterization. - Xinyang Jiang; Lu Liu 019; Caihua Shan; Yifei Shen; Xuanyi Dong; Dongsheng Li 002 (NeurIPS, 2021)

Reinforcement Learning Enhanced Explainer for Graph Neural Networks. - Caihua Shan; Yifei Shen; Yao Zhang 009; Xiang Li 067; Dongsheng Li 002 (NeurIPS, 2021)

On Analyzing Graphs with Motif-Paths. - Xiaodong Li 009; Reynold Cheng; Kevin Chen-Chuan Chang; Caihua Shan; Chenhao Ma 001; Hongtai Cao (Proc. VLDB Endow., 2021)

RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation. - Yao Zhang 009; Yun Xiong; Yiheng Sun; Caihua Shan; Tian Lu; Hui Song; Yangyong Zhu (CIKM, 2022)

RendNet: Unified 2D/3D Recognizer with Latent Space Rendering. - Ruoxi Shi; Xinyang Jiang; Caihua Shan; Yansen Wang; Dongsheng Li 002 (CVPR, 2022)

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily. - Xiang Li 067; Renyu Zhu; Yao Cheng; Caihua Shan; Siqiang Luo; Dongsheng Li 002; Weining Qian (ICML, 2022)

CLARE: A Semi-supervised Community Detection Algorithm. - Xixi Wu; Yun Xiong; Yao Zhang 009; Yizhu Jiao; Caihua Shan; Yiheng Sun; Yangyong Zhu; Philip S. Yu (KDD, 2022)

CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis. - Shifu Yan; Caihua Shan; Wenyi Yang; Bixiong Xu; Dongsheng Li 002; Lili Qiu; Jie Tong; Qi Zhang 001 (KDD, 2022)

Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling. - Yuchen Fang; Kan Ren; Caihua Shan; Yifei Shen; You Li; Weinan Zhang 001; Yong Yu 001; Dongsheng Li 002 (AAAI, 2023)

COCLEP: Contrastive Learning-based Semi-Supervised Community Search. - Ling Li; Siqiang Luo; Yuhai Zhao; Caihua Shan; Zhengkui Wang; Lu Qin 001 (ICDE, 2023)

Explaining Temporal Graph Models through an Explorer-Navigator Framework. - Wenwen Xia; Mincai Lai; Caihua Shan; Yao Zhang 009; Xinnan Dai; Xiang Li 067; Dongsheng Li 002 (ICLR, 2023)

CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling. - Yansen Wang; Xinyang Jiang; Kan Ren; Caihua Shan; Xufang Luo; Dongqi Han; Kaitao Song; Yifei Shen; Dongsheng Li 002 (ICML, 2023)

SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking. - Xiang Li 067; Tiandi Ye; Caihua Shan; Dongsheng Li 002; Ming Gao 001 (WWW, 2023)

Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking. - Xiang Li 067; Tiandi Ye; Caihua Shan; Dongsheng Li 002; Ming Gao 001 (CoRR, 2023)

Biological Factor Regulatory Neural Network. - Xinnan Dai; Caihua Shan; Jie Zheng; Xiaoxiao Li; Dongsheng Li 002 (CoRR, 2023)

Label Propagation for Graph Label Noise. - Yao Cheng; Caihua Shan; Yifei Shen; Xiang Li 067; Siqiang Luo; Dongsheng Li 002 (CoRR, 2023)

Prioritized Propagation in Graph Neural Networks. - Yao Cheng; Minjie Chen; Xiang Li 067; Caihua Shan; Ming Gao 001 (CoRR, 2023)

AdaMedGraph: Adaboosting Graph Neural Networks for Personalized Medicine. - Jie Lian; Xufang Luo; Caihua Shan; Dongqi Han; Varut Vardhanabhuti; Dongsheng Li 002 (CoRR, 2023)

Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads. - Dingheng Mo; Fanchao Chen; Siqiang Luo; Caihua Shan (Proc. ACM Manag. Data, 2023)

Training-free Multi-objective Diffusion Model for 3D Molecule Generation. - Xu Han; Caihua Shan; Yifei Shen; Can Xu; Han Yang; Xiang Li 067; Dongsheng Li 002 (ICLR, 2024)

Resurrecting Label Propagation for Graphs with Heterophily and Label Noise. - Yao Cheng; Caihua Shan; Yifei Shen; Xiang Li 067; Siqiang Luo; Dongsheng Li 002 (KDD, 2024)

Can Graph Learning Improve Planning in LLM-based Agents? - Xixi Wu; Yifei Shen; Caihua Shan; Kaitao Song; Siwei Wang; Bohang Zhang; Jiarui Feng; Hong Cheng; Wei Chen; Yun Xiong; Dongsheng Li (NeurIPS, 2024)

Towards Learning from Graphs with Heterophily: Progress and Future. - Chenghua Gong; Yao Cheng; Jianxiang Yu 001; Can Xu; Caihua Shan; Siqiang Luo; Xiang Li 067 (CoRR, 2024)

Can Graph Learning Improve Task Planning? - Xixi Wu; Yifei Shen; Caihua Shan; Kaitao Song; Siwei Wang; Bohang Zhang; Jiarui Feng; Hong Cheng; Wei Chen; Yun Xiong; Dongsheng Li (CoRR, 2024)

Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path. - Xinnan Dai; Qihao Wen; Yifei Shen; Hongzhi Wen; Dongsheng Li 002; Jiliang Tang; Caihua Shan (CoRR, 2024)

How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension. - Xinnan Dai; Haohao Qu; Yifen Shen; Bohang Zhang; Qihao Wen; Wenqi Fan; Dongsheng Li 002; Jiliang Tang; Caihua Shan (CoRR, 2024)

Hierarchically Recognizing Vector Graphics and A New Chart-Based Vector Graphics Dataset. - Shuguang Dou; Xinyang Jiang; Lu Liu 019; Lu Ying; Caihua Shan; Yifei Shen; Xuanyi Dong; Yun Wang 012; Dongsheng Li 002; Cairong Zhao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Learning Prioritized Node-Wise Message Propagation in Graph Neural Networks. - Yao Cheng; Minjie Chen; Caihua Shan; Xiang Li (IEEE Trans. Knowl. Data Eng., 2024)

Learning Prioritized Node-Wise Message Propagation in Graph Neural Networks (Extended Abstract). - Yao Cheng; Minjie Chen; Caihua Shan; Xiang Li 067 (ICDE, 2025)

How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension. - Xinnan Dai; Haohao Qu; Yifei Shen; Bohang Zhang; Qihao Wen; Wenqi Fan; Dongsheng Li 002; Jiliang Tang; Caihua Shan (ICLR, 2025)

CauseRuDi: Explaining Behavior Sequence Models by Causal Statistics Generation and Rule Distillation. - Yao Zhang 009; Yun Xiong; Yiheng Sun; Yucheng Jin; Caihua Shan; Tian Lu; Hui Song; Shengli Sun (IEEE Trans. Knowl. Data Eng., 2025)

A Comprehensive Analysis on LLM-based Node Classification Algorithms. - Xixi Wu; Yifei Shen; Fangzhou Ge; Caihua Shan; Yizhu Jiao; Xiangguo Sun; Hong Cheng 001 (CoRR, 2025)

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning. - Zehui Li; Vallijah Subasri; Yifei Shen; Dongsheng Li; Yiren Zhao; Guy-Bart Stan; Caihua Shan (CoRR, 2025)

Chain-of-Model Learning for Language Model. - Kaitao Song; Xiaohua Wang; Xu Tan 003; Huiqiang Jiang; Chengruidong Zhang; Yongliang Shen 001; Cen LU; Zihao Li 006; Zifan Song; Caihua Shan; Yansen Wang; Kan Ren; et al. (CoRR, 2025)