Learning Towards Emergence: Paving the Way to Induce Emergence by Inhibiting Monosemantic Neurons on Pre-trained Models[LLM][Emergence] Jiachuan WANG, Shimin DI, Tianhao TANG, Haoyang LI, Charles Wang-wai NG, Xiaofang ZHOU, Lei CHEN
A Pilot Empirical Study on When and How to Use Knowledge Graphs as Retrieval Augmented Generation[LLM][KG][RAG] Xujie Yuan, Yongxu Liu, Shimin Di, Shiwen Wu, Libin Zheng, Rui Meng, Lei Chen, Xiaofang Zhou, Jian Yin
Beyond Path Selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R)GRPO[LLM][IE] Ran Li, Shimin Di, Yuchen Liu, Chen Jing, Yu Qiu, Lei Chen
ESCFD: Probabilistic Flow Diffusion Model for Accelerated High-Quality Single-Cell RNA-seq Data Synthesis[AI4Sci]
31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2025)
Shuangyin LI, JiHua YANG, Yixuan WANG, Shimin DI, Lei CHEN
Structuring Benchmark into Knowledge Graphs to Assist Large Language Models in Retrieving and Designing Models[N-Auto][LLM][KG]
13rd International Conference on Learning Representations (ICLR 2025)
Hanmo LIU, Shimin DI*, Jialiang WANG, Zhili WANG, Jiachuan WANG, Xiaofang ZHOU, Lei CHEN
Efficient Latent-based Scoring Function Search for N-ary Relational Knowledge Bases[KG] ACM Transactions on Knowledge Discovery from Data (TKDD 2024) Shimin DI, Quanming YAO, Yongqi ZHANG*, Xiaofang ZHOU, Lei CHEN
A Universal and Interpretable Method for Enhancing Stock Price Prediction 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024) Yuchen LIU, Shimin DI*, Lei CHEN, Xiaofang ZHOU and Fei LIN
Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks[LLM][Emergence] 30TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2024) Jiachuan WANG, Shimin DI*, Lei CHEN, Charles Wang-wai NG
SimDiff: Simple Denoising Probabilistic Latent Diffusion Model for data augmentation on Multi-modal Knowledge Graph[KG] 30TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2024) Ran LI, Shimin DI*, Lei CHEN, Xiaofang ZHOU
Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense[GNN][Adversarial] 50TH International Conference on Very Large Databases (VLDB 2024) Haoyang LI, Shimin DI*, Calvin LI, Lei CHEN, Xiaofang ZHOU
GradGCL: Gradient Graph Contrastive Learning[GNN][Contrastive] 40TH IEEE International Conference on Data Engineering (ICDE 2024) Ran LI, Shimin DI*, Lei CHEN, Xiaofang ZHOU
Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks[AutoGNN] 40TH IEEE International Conference on Data Engineering (ICDE 2024) Zhili WANG, Shimin DI*, Lei CHEN, Xiaofang ZHOU
E2GCL: Efficient and Expressive Contrastive Learning on Graph Neural Networks[GNN][Contrastive] 40TH IEEE International Conference on Data Engineering (ICDE 2024) Haoyang LI, Shimin DI*, Lei CHEN, Xiaofang ZHOU
Effective Data Selection and Replay for Unsupervised Continual Learning 40TH IEEE International Conference on Data Engineering (ICDE 2024) Hanmo LIU, Shimin DI*, Haoyang LI, Shuangyin LI, Lei CHEN, Xiaofang ZHOU
Noise2Info: Noisy Image to Information of Noise for Self-Supervised Image Denoising Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023) Jiachuan WANG, Shimin DI*, Lei CHEN, Charles Wang Wai NG
A Message Passing Neural Network Space for Better Capturing Data-dependent Receptive Fields[AutoGNN] 29TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023) Zhili WANG, Shimin DI*, Lei CHEN
Revisiting Injective Attacks on Recommender Systems[Adversarial] 36TH Advances in Neural Information Processing Systems (NeurIPS 2022) Haoyang LI, Shimin DI*, Lei CHEN
Black-box Adversarial Attack and Defense on Graph Neural Networks[GNN][Adversarial] IEEE 38th International Conference on Data Engineering (ICDE 2022) Haoyang LI, Shimin DI*, Zijian LI, Lei CHEN, Jiannong CAO
Searching to Sparsify Tensor Decomposition for N-ary Relational Data[KG] 30TH Proceedings of the ACM Web Conference (WWW 2021) Shimin DI, Quanming YAO*, Lei CHEN
Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding[KG] IEEE 37th International Conference on Data Engineering (ICDE 2021) Shimin DI, Yongqi ZHANG, Quanming YAO*, Lei CHEN
AutoGEL: An Automated Graph Neural Network with Explicit Link Information[AutoGNN] 35TH Advances in Neural Information Processing Systems (NeurIPS 2021) Zhili WANG, Shimin DI*, Lei CHEN
FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection 14TH ACM International Conference on Web Search and Data Mining (WSDM 2021) Jia LI, Shimin DI, Yanyan SHEN*, Lei CHEN
Relation Extraction via Domain-aware Transfer Learning[IE][KG] 25TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2019) Shimin DI, Yanyan SHEN*, Lei CHEN
Transfer Learning via Feature Isomorphism Discovery 24TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2018) Shimin DI, Jingshu PENG, Yanyan SHEN*, Lei CHEN