| Network In Network M Lin, Q Chen, S Yan International Conference on Learning Representations, 2013 | 10810 | 2013 |
| Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ... | 3086 | 2015 |
| On the spectral bias of neural networks N Rahaman, A Baratin, D Arpit, F Draxler, M Lin, F Hamprecht, Y Bengio, ... International conference on machine learning, 5301-5310, 2019 | 2421 | 2019 |
| Gradient based sample selection for online continual learning R Aljundi, M Lin, B Goujaud, Y Bengio Advances in neural information processing systems 32, 2019 | 1273 | 2019 |
| Online continual learning with maximal interfered retrieval R Aljundi, E Belilovsky, T Tuytelaars, L Charlin, M Caccia, M Lin, ... Advances in neural information processing systems 32, 2019 | 799 | 2019 |
| HCP: A Flexible CNN Framework for Multi-label Image Classification Y Wei, W Xia, M Lin, J Huang, B Ni, J Dong, Y Zhao, S Yan IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 | 766 | 2015 |
| Understanding r1-zero-like training: A critical perspective Z Liu, C Chen, W Li, P Qi, T Pang, C Du, WS Lee, M Lin arXiv preprint arXiv:2503.20783, 2025 | 479 | 2025 |
| Better diffusion models further improve adversarial training Z Wang, T Pang, C Du, M Lin, W Liu, S Yan International conference on machine learning, 36246-36263, 2023 | 375 | 2023 |
| On evaluating adversarial robustness of large vision-language models Y Zhao, T Pang, C Du, X Yang, C Li, NMM Cheung, M Lin Advances in Neural Information Processing Systems 36, 54111-54138, 2023 | 373 | 2023 |
| Lorahub: Efficient cross-task generalization via dynamic lora composition C Huang, Q Liu, BY Lin, T Pang, C Du, M Lin arXiv preprint arXiv:2307.13269, 2023 | 326 | 2023 |
| Causal attention for interpretable and generalizable graph classification Y Sui, X Wang, J Wu, M Lin, X He, TS Chua Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 270 | 2022 |
| NUS-PRO: A New Visual Tracking Challenge A Li, M Lin, Y Wu, MH Yang, S Yan IEEE transactions on pattern analysis and machine intelligence 38, 335--349, 2016 | 231 | 2016 |
| A recipe for watermarking diffusion models Y Zhao, T Pang, C Du, X Yang, NM Cheung, M Lin arXiv preprint arXiv:2303.10137, 2023 | 215 | 2023 |
| Robustness and accuracy could be reconcilable by (proper) definition T Pang, M Lin, X Yang, J Zhu, S Yan International conference on machine learning, 17258-17277, 2022 | 204 | 2022 |
| Online fast adaptation and knowledge accumulation (osaka): a new approach to continual learning M Caccia, P Rodriguez, O Ostapenko, F Normandin, M Lin, ... Advances in Neural Information Processing Systems 33, 16532-16545, 2020 | 188* | 2020 |
| Causal representation learning for out-of-distribution recommendation W Wang, X Lin, F Feng, X He, M Lin, TS Chua Proceedings of the ACM Web Conference 2022, 3562-3571, 2022 | 148 | 2022 |
| Chain of preference optimization: Improving chain-of-thought reasoning in llms X Zhang, C Du, T Pang, Q Liu, W Gao, M Lin Advances in Neural Information Processing Systems 37, 333-356, 2024 | 138 | 2024 |
| Agent smith: A single image can jailbreak one million multimodal llm agents exponentially fast X Gu, X Zheng, T Pang, C Du, Q Liu, Y Wang, J Jiang, M Lin arXiv preprint arXiv:2402.08567, 2024 | 126 | 2024 |
| Improved techniques for optimization-based jailbreaking on large language models X Jia, T Pang, C Du, Y Huang, J Gu, Y Liu, X Cao, M Lin arXiv preprint arXiv:2405.21018, 2024 | 118 | 2024 |
| Zero bubble pipeline parallelism P Qi, X Wan, G Huang, M Lin arXiv preprint arXiv:2401.10241, 2023 | 114* | 2023 |
Shuicheng Yan, e-AGI: efficient, embo...Professor@National University of Singapore | Looking for lab members targeting beyond papersVerified email at nus.edu.sg
