| 2024 | ACL | Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression. | Peiyu Liu, Ze-Feng Gao, Xin Zhao, Yipeng Ma, Tao Wang, Ji-Rong Wen |
| 2024 | COLING | Enhancing Parameter-efficient Fine-tuning with Simple Calibration Based on Stable Rank. | Peiyu Liu, Ze-Feng Gao, Xiao Zhang, Wayne Xin Zhao, Ji-Rong Wen |
| 2024 | COLING | Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study. | Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen |
| 2023 | ACL | Small Pre-trained Language Models Can be Fine-tuned as Large Models via Over-Parameterization. | Ze-Feng Gao, Kun Zhou, Peiyu Liu, Wayne Xin Zhao, Ji-Rong Wen |
| 2023 | EMNLP | Enhancing Scalability of Pre-trained Language Models via Efficient Parameter Sharing. | Peiyu Liu, Ze-Feng Gao, Yushuo Chen, Xin Zhao, Ji-Rong Wen |
| 2022 | COLING | Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models. | Ze-Feng Gao, Peiyu Liu, Wayne Xin Zhao, Zhong-Yi Lu, Ji-Rong Wen |
| 2021 | ACL | Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators. | Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao, Zhi-Yuan Xie, Zhong-Yi Lu, Ji-Rong Wen |