| QDrop: randomly dropping quantization for extremely low-bit post-training quantization X Wei, R Gong, Y Li, X Liu, F Yu International Conference on Learning Representations 2022, 2022 | 98 | 2022 |
| Outlier suppression: Pushing the limit of low-bit transformer language models X Wei, Y Zhang, X Zhang, R Gong, S Zhang, Q Zhang, F Yu, X Liu Advances in Neural Information Processing Systems 35, 17402-17414, 2022 | 77 | 2022 |
| Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling X Wei, Y Zhang, Y Li, X Zhang, R Gong, J Guo, X Liu arXiv preprint arXiv:2304.09145, 2023 | 58 | 2023 |
| Qllm: Accurate and efficient low-bitwidth quantization for large language models J Liu, R Gong, X Wei, Z Dong, J Cai, B Zhuang arXiv preprint arXiv:2310.08041, 2023 | 26 | 2023 |
| Lossy and Lossless (L) Post-training Model Size Compression Y Shi, S Bai, X Wei, R Gong, J Yang arXiv preprint arXiv:2308.04269, 2023 | 1 | 2023 |
