| GraphMAE2: A decoding-enhanced masked self-supervised graph learner Z Hou, Y He, Y Cen, X Liu, Y Dong, E Kharlamov, J Tang WWW 2023, 2023 | 112 | 2023 |
| UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs Y He, Y Sui, X He, B Hooi KDD 2025, 2025 | 25* | 2025 |
| Improving the training of graph neural networks with consistency regularization C Zhang, Y He, Y Cen, Z Hou, J Tang arXiv preprint arXiv:2112.04319, 2021 | 13 | 2021 |
| SCR: Training graph neural networks with consistency regularization C Zhang, Y He, Y Cen, Z Hou, W Feng, Y Dong, X Cheng, H Cai, F He, ... arXiv preprint arXiv:2112.04319, 2021 | 8 | 2021 |
| Fidelis: Faithful reasoning in large language model for knowledge graph question answering Y Sui, Y He, N Liu, X He, K Wang, B Hooi arXiv preprint arXiv:2405.13873, 2024 | 7 | 2024 |
| SGKD: A scalable and effective knowledge distillation framework for graph representation learning Y He, Y Ma ICDM Workshops 2022, 2022 | 6 | 2022 |
| Generalizing Graph Transformers Across Diverse Graphs and Tasks via Pre-Training on Industrial-Scale Data Y He, Z Hou, Y Cen, F He, X Cheng, B Hooi arXiv preprint arXiv:2407.03953, 2024 | 3 | 2024 |
| Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study over Open-ended Question Answering Y Sui, Y He, Z Ding, B Hooi arXiv preprint arXiv:2410.08085, 2024 | 2 | 2024 |
| UniGraph2: Learning a Unified Embedding Space to Bind Multimodal Graphs Y He, Y Sui, X He, Y Liu, Y Sun, B Hooi WWW 2025, 2025 | 1 | 2025 |
| MDGNN: Metapath-based decoupled graph neural network for MAG240M-LSC H Zhao, Y Cen, Y He, Z Hou, X Liu, X Cheng Conf. Neural Inf. Process. Syst, 2024 | 1 | 2024 |
| Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models Y Sui, Y He, T Cao, S Han, B Hooi arXiv preprint arXiv:2502.19918, 2025 | | 2025 |
| Can Indirect Prompt Injection Attacks Be Detected and Removed? Y Chen, H Li, Y Sui, Y He, Y Liu, Y Song, B Hooi arXiv preprint arXiv:2502.16580, 2025 | | 2025 |
| Evaluating the Paperclip Maximizer: Are RL-Based Language Models More Likely to Pursue Instrumental Goals? Y He, Y Li, J Wu, Y Sui, Y Chen, B Hooi arXiv preprint arXiv:2502.12206, 2025 | | 2025 |
Yukuo CenZhipu AI, Tsinghua UniversityVerifisert e-postadresse på zhipuai.cn
