Caihua Shan

58 papers A* 20A 4Journal 33Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
UniG2U-Bench: Do Unified Models Advance Multimodal Understanding?
CoRR
Zimo Wen, Boxiu Li, Wanbo Zhang, Junxiang Lei, Xiaoyu Chen, Yijia Fan, Qi Zhang, Yujiang Wang, Lili Qiu, Bo Li, Ziwei Liu, Caihua Shan, Yifan Yang, Yifei Shen
2025 J jnl
A Comprehensive Analysis on LLM-based Node Classification Algorithms.
CoRR
Xixi Wu, Yifei Shen, Fangzhou Ge, Caihua Shan, Yizhu Jiao, Xiangguo Sun, Hong Cheng
2025 J jnl
CauseRuDi: Explaining Behavior Sequence Models by Causal Statistics Generation and Rule Distillation.
IEEE Trans. Knowl. Data Eng.
Yao Zhang, Yun Xiong, Yiheng Sun, Yucheng Jin, Caihua Shan, Tian Lu, Hui Song, Shengli Sun
2025 J jnl
Chain-of-Model Learning for Language Model.
CoRR
Kaitao Song, Xiaohua Wang, Xu Tan, Huiqiang Jiang, Chengruidong Zhang, Yongliang Shen, Cen Lu, Zihao Li, Zifan Song, Caihua Shan, Yansen Wang, Kan Ren, Xiaoqing Zheng, Tao Qin, Yuqing Yang, Dongsheng Li, Lili Qiu
2025 A* conf
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension.
ICLR
Xinnan Dai, Haohao Qu, Yifei Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan
2025 A* conf
Learning Prioritized Node-Wise Message Propagation in Graph Neural Networks (Extended Abstract).
ICDE
Yao Cheng, Minjie Chen, Caihua Shan, Xiang Li
2025 J jnl
Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning.
CoRR
Zehui Li, Vallijah Subasri, Yifei Shen, Dongsheng Li, Yiren Zhao, Guy-Bart Stan, Caihua Shan
2025 J jnl
VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL.
CoRR
Kyoungjun Park, Yifan Yang, Juheon Yi, Shicheng Zheng, Yifei Shen, Dongqi Han, Caihua Shan, Muhammad Muaz, Lili Qiu
2025 A* conf
When Do LLMs Help With Node Classification? A Comprehensive Analysis.
ICML
Xixi Wu, Yifei Shen, Fangzhou Ge, Caihua Shan, Yizhu Jiao, Xiangguo Sun, Hong Cheng
2024 A* conf
Can Graph Learning Improve Planning in LLM-based Agents?
NeurIPS
Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li
2024 J jnl
Can Graph Learning Improve Task Planning?
CoRR
Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li
2024 J jnl
Hierarchically Recognizing Vector Graphics and A New Chart-Based Vector Graphics Dataset.
IEEE Trans. Pattern Anal. Mach. Intell.
Shuguang Dou, Xinyang Jiang, Lu Liu, Lu Ying, Caihua Shan, Yifei Shen, Xuanyi Dong, Yun Wang, Dongsheng Li, Cairong Zhao
2024 J jnl
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension.
CoRR
Xinnan Dai, Haohao Qu, Yifen Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan
2024 J jnl
Learning Prioritized Node-Wise Message Propagation in Graph Neural Networks.
IEEE Trans. Knowl. Data Eng.
Yao Cheng, Minjie Chen, Caihua Shan, Xiang Li
2024 A* conf
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise.
KDD
Yao Cheng, Caihua Shan, Yifei Shen, Xiang Li, Siqiang Luo, Dongsheng Li
2024 J jnl
Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path.
CoRR
Xinnan Dai, Qihao Wen, Yifei Shen, Hongzhi Wen, Dongsheng Li, Jiliang Tang, Caihua Shan
2024 J jnl
Towards Learning from Graphs with Heterophily: Progress and Future.
CoRR
Chenghua Gong, Yao Cheng, Jianxiang Yu, Can Xu, Caihua Shan, Siqiang Luo, Xiang Li
2024 A* conf
Training-free Multi-objective Diffusion Model for 3D Molecule Generation.
ICLR
Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
2023 J jnl
AdaMedGraph: Adaboosting Graph Neural Networks for Personalized Medicine.
CoRR
Jie Lian, Xufang Luo, Caihua Shan, Dongqi Han, Varut Vardhanabhuti, Dongsheng Li
2023 J jnl
Biological Factor Regulatory Neural Network.
CoRR
Xinnan Dai, Caihua Shan, Jie Zheng, Xiaoxiao Li, Dongsheng Li
2023 A* conf
COCLEP: Contrastive Learning-based Semi-Supervised Community Search.
ICDE
Ling Li, Siqiang Luo, Yuhai Zhao, Caihua Shan, Zhengkui Wang, Lu Qin
2023 A* conf
CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling.
ICML
Yansen Wang, Xinyang Jiang, Kan Ren, Caihua Shan, Xufang Luo, Dongqi Han, Kaitao Song, Yifei Shen, Dongsheng Li
2023 A* conf
Explaining Temporal Graph Models through an Explorer-Navigator Framework.
ICLR
Wenwen Xia, Mincai Lai, Caihua Shan, Yao Zhang, Xinnan Dai, Xiang Li, Dongsheng Li
2023 J jnl
Label Propagation for Graph Label Noise.
CoRR
Yao Cheng, Caihua Shan, Yifei Shen, Xiang Li, Siqiang Luo, Dongsheng Li
2023 A* conf
Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling.
AAAI
Yuchen Fang, Kan Ren, Caihua Shan, Yifei Shen, You Li, Weinan Zhang, Yong Yu, Dongsheng Li
2023 J jnl
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads.
CoRR
Dingheng Mo, Fanchao Chen, Siqiang Luo, Caihua Shan
2023 J jnl
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads.
Proc. ACM Manag. Data
Dingheng Mo, Fanchao Chen, Siqiang Luo, Caihua Shan
2023 J jnl
Prioritized Propagation in Graph Neural Networks.
CoRR
Yao Cheng, Minjie Chen, Xiang Li, Caihua Shan, Ming Gao
2023 A* conf
SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking.
WWW
Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
2023 J jnl
Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking.
CoRR
Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
2022 A* conf
CLARE: A Semi-supervised Community Detection Algorithm.
KDD
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Caihua Shan, Yiheng Sun, Yangyong Zhu, Philip S. Yu
2022 J jnl
CLARE: A Semi-supervised Community Detection Algorithm.
CoRR
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Caihua Shan, Yiheng Sun, Yangyong Zhu, Philip S. Yu
2022 A* conf
CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis.
KDD
Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang
2022 J jnl
CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis.
CoRR
Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang
2022 A* conf
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily.
ICML
Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
2022 J jnl
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily.
CoRR
Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
2022 J jnl
RendNet: Unified 2D/3D Recognizer With Latent Space Rendering.
CoRR
Ruoxi Shi, Xinyang Jiang, Caihua Shan, Yansen Wang, Dongsheng Li
2022 A* conf
RendNet: Unified 2D/3D Recognizer with Latent Space Rendering.
CVPR
Ruoxi Shi, Xinyang Jiang, Caihua Shan, Yansen Wang, Dongsheng Li
2022 A conf
RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation.
CIKM
Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu
2022 J jnl
RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation.
CoRR
Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu
2021 A conf
CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph.
CIKM
Yao Zhang, Yun Xiong, Dongsheng Li, Caihua Shan, Kan Ren, Yangyong Zhu
2021 A conf
How Powerful is Graph Convolution for Recommendation?
CIKM
Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled B. Letaief, Dongsheng Li
2021 J jnl
How Powerful is Graph Convolution for Recommendation?
CoRR
Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled B. Letaief, Dongsheng Li
2021 J jnl
On Analyzing Graphs with Motif-Paths.
Proc. VLDB Endow.
Xiaodong Li, Reynold Cheng, Kevin Chen-Chuan Chang, Caihua Shan, Chenhao Ma, Hongtai Cao
2021 A* conf
Recognizing Vector Graphics without Rasterization.
NeurIPS
Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li
2021 J jnl
Recognizing Vector Graphics without Rasterization.
CoRR
Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li
2021 A* conf
Reinforcement Learning Enhanced Explainer for Graph Neural Networks.
NeurIPS
Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li
2020 J jnl
A Crowdsourcing Framework for Collecting Tabular Data.
IEEE Trans. Knowl. Data Eng.
Caihua Shan, Nikos Mamoulis, Guoliang Li, Reynold Cheng, Zhipeng Huang, Yudian Zheng
2020 — conf
A General Early-Stopping Module for Crowdsourced Ranking.
DASFAA (2)
Caihua Shan, Leong Hou U, Nikos Mamoulis, Reynold Cheng, Xiang Li
2020 A conf
A Toolkit for Managing Multiple Crowdsourced Top-K Queries.
CIKM
Caihua Shan, Leong Hou U, Nikos Mamoulis, Reynold Cheng
2020 A* conf
An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms.
ICDE
Caihua Shan, Nikos Mamoulis, Reynold Cheng, Guoliang Li, Xiang Li, Yuqiu Qian
2020 A* conf
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data.
KDD
Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester
2020 J jnl
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data.
CoRR
Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester
2019 J jnl
A General Early-Stopping Module for Crowdsourced Ranking.
CoRR
Caihua Shan, Leong Hou U, Nikos Mamoulis, Reynold Cheng, Xiang Li
2019 J jnl
An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms.
CoRR
Caihua Shan, Nikos Mamoulis, Reynold Cheng, Guoliang Li, Xiang Li, Yuqiu Qian
2018 A* conf
T-Crowd: Effective Crowdsourcing for Tabular Data.
ICDE
Caihua Shan, Nikos Mamoulis, Guoliang Li, Reynold Cheng, Zhipeng Huang, Yudian Zheng
2017 J jnl
T-Crowd: Effective Crowdsourcing for Tabular Data.
CoRR
Caihua Shan, Nikos Mamoulis, Guoliang Li, Reynold Cheng, Zhipeng Huang, Yudian Zheng
2017 J jnl
Truth Inference in Crowdsourcing: Is the Problem Solved?
Proc. VLDB Endow.
Yudian Zheng, Guoliang Li, Yuanbing Li, Caihua Shan, Reynold Cheng