| Omniquant: Omnidirectionally calibrated quantization for large language models W Shao*, M Chen*, Z Zhang, P Xu, L Zhao, Z Li, K Zhang, P Gao, Y Qiao, ... ICLR2024 spotlight (* equal contribution), 2023 | 180 | 2023 |
| Cf-vit: A general coarse-to-fine method for vision transformer M Chen, M Lin, K Li, Y Shen, Y Wu, F Chao, R Ji AAAI 2023 Oral, 2023 | 72 | 2023 |
| Diffrate: Differentiable compression rate for efficient vision transformers M Chen, W Shao, P Xu, M Lin, K Zhang, F Chao, R Ji, Y Qiao, P Luo ICCV 2023, 2023 | 45 | 2023 |
| Super vision transformer M Lin*, M Chen*, Y Zhang, C Shen, R Ji, L Cao IJCV 2023 (* equal contribution), 2023 | 27 | 2023 |
| Efficientqat: Efficient quantization-aware training for large language models M Chen, W Shao, P Xu, J Wang, P Gao, K Zhang, P Luo arXiv preprint arXiv:2407.11062, 2024 | 23 | 2024 |
| Fine-grained data distribution alignment for post-training quantization Y Zhong, M Lin, M Chen, K Li, Y Shen, F Chao, Y Wu, R Ji ECCV 2022, 2022 | 21 | 2022 |
| Smmix: Self-motivated image mixing for vision transformers M Chen, M Lin, Z Lin, Y Zhang, F Chao, R Ji ICCV 2023, 2023 | 12 | 2023 |
| Besa: Pruning large language models with blockwise parameter-efficient sparsity allocation P Xu, W Shao, M Chen, S Tang, K Zhang, P Gao, F An, Y Qiao, P Luo ICLR 2024, 2024 | 10 | 2024 |
| I&S-ViT: An Inclusive & Stable Method for Pushing the Limit of Post-Training ViTs Quantization Y Zhong, J Hu, M Lin, M Chen, R Ji arXiv preprint arXiv:2311.10126, 2023 | 7 | 2023 |
| OptG: Optimizing Gradient-driven Criteria in Network Sparsity Y Zhang, M Lin, M Chen, F Chao, R Ji arXiv preprint arXiv:2201.12826, 2022 | 4 | 2022 |
| Adapting llama decoder to vision transformer J Wang, W Shao, M Chen, C Wu, Y Liu, T Wu, K Zhang, S Zhang, K Chen, ... arXiv preprint arXiv:2404.06773, 2024 | 3 | 2024 |
| PrefixQuant: Static Quantization Beats Dynamic through Prefixed Outliers in LLMs M Chen, Y Liu, J Wang, Y Bin, W Shao, P Luo arXiv preprint arXiv:2410.05265, 2024 | 2 | 2024 |
Ping Luo (羅平)Associate Professor, The University of Hong Kong; MMLAB@HKU確認したメール アドレス: hku.hk