| 2026 | AAAI | Beyond Retraining: Training-Free Unknown Class Filtering for Source-Free Open Set Domain Adaptation of Vision-Language Models. | Yongguang Li, Jindong Li, Qi Wang, Qianli Xing, Runliang Niu, Shengsheng Wang, Menglin Yang |
| 2026 | ACL | Self-Reflective Generation at Test Time. | Jian Mu, Qixin Zhang, Zhiyong Wang, Menglin Yang, Shuang Qiu, Chengwei Qin, Zhongxiang Dai, Yao Shu |
| 2026 | ACL | HeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents. | Jinchang Zhu, Jindong Li, Cheng Zhang, Jiahong Liu, Menglin Yang |
| 2025 | CVPR | Understanding Fine-tuning CLIP for Open-vocabulary Semantic Segmentation in Hyperbolic Space. | Zelin Peng, Zhengqin Xu, Zhilin Zeng, Changsong Wen, Yu Huang, Menglin Yang, Feilong Tang, Wei Shen |
| 2025 | ICML | Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. | Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao |
| 2025 | KDD | Lorentzian Residual Neural Networks. | Neil He, Menglin Yang, Rex Ying |
| 2025 | KDD | Hyperbolic Deep Learning for Foundation Models: A Survey. | Neil He, Hiren Madhu, Ngoc Bui, Menglin Yang, Rex Ying |
| 2025 | KDD | Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning. | Yifei Zhang, Hao Zhu, Menglin Yang, Jiahong Liu, Rex Ying, Irwin King, Piotr Koniusz |
| 2025 | WWW | Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks. | Menglin Yang, Yifei Zhang, Jialin Chen, Melanie Weber, Rex Ying |
| 2024 | KDD | Hypformer: Exploring Efficient Transformer Fully in Hyperbolic Space. | Menglin Yang, Harshit Verma, Delvin Ce Zhang, Jiahong Liu, Irwin King, Rex Ying |
| 2024 | WWW | Text-Attributed Graph Representation Learning: Methods, Applications, and Challenges. | Delvin Ce Zhang, Menglin Yang, Rex Ying, Hady W. Lauw |
| 2023 | ICML | Hyperbolic Representation Learning: Revisiting and Advancing. | Menglin Yang, Min Zhou, Rex Ying, Yankai Chen, Irwin King |
| 2023 | KDD | κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning. | Menglin Yang, Min Zhou, Lujia Pan, Irwin King |
| 2023 | KDD | Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications. | Min Zhou, Menglin Yang, Bo Xiong, Hui Xiong, Irwin King |
| 2023 | SIGIR | WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering. | Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King |
| 2022 | ICDE | Discovering Representative Attribute-stars via Minimum Description Length. | Jiahong Liu, Min Zhou, Philippe Fournier-Viger, Menglin Yang, Lujia Pan, Mourad Nouioua |
| 2022 | KDD | HICF: Hyperbolic Informative Collaborative Filtering. | Menglin Yang, Zhihao Li, Min Zhou, Jiahong Liu, Irwin King |
| 2022 | WWW | HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization. | Menglin Yang, Min Zhou, Jiahong Liu, Defu Lian, Irwin King |
| 2022 | SIGIR | BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction. | Bisheng Li, Min Zhou, Shengzhong Zhang, Menglin Yang, Defu Lian, Zengfeng Huang |
| 2022 | WSDM | Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation. | Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King |
| 2021 | KDD | Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space. | Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King |
| 2020 | ICDM | FeatureNorm: L2 Feature Normalization for Dynamic Graph Embedding. | Menglin Yang, Ziqiao Meng, Irwin King |