QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization. - Xiuying Wei; Ruihao Gong; Yuhang Li 001; Xianglong Liu 001; Fengwei Yu (ICLR, 2022)

Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models. - Xiuying Wei; Yunchen Zhang; Xiangguo Zhang; Ruihao Gong; Shanghang Zhang; Qi Zhang; Fengwei Yu; Xianglong Liu 001 (NeurIPS, 2022)

Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling. - Xiuying Wei; Yunchen Zhang; Yuhang Li 001; Xiangguo Zhang; Ruihao Gong; Jinyang Guo; Xianglong Liu 001 (EMNLP, 2023)

Lossy and Lossless (L2) Post-training Model Size Compression. - Yumeng Shi; Shihao Bai; Xiuying Wei; Ruihao Gong; Jianlei Yang 001 (ICCV, 2023)

Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling. - Xiuying Wei; Yunchen Zhang; Yuhang Li 001; Xiangguo Zhang; Ruihao Gong; Jinyang Guo; Xianglong Liu 001 (CoRR, 2023)

Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection. - Yunqian Fan; Xiuying Wei; Ruihao Gong; Yuqing Ma; Xiangguo Zhang; Qi Zhang; Xianglong Liu 001 (AAAI, 2024)

Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes. - Ruihao Gong; Yang Yong; Zining Wang; Jinyang Guo; Xiuying Wei; Yuqing Ma; Xianglong Liu 001 (AAAI, 2024)

QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models. - Jing Liu; Ruihao Gong; Xiuying Wei; Zhiwei Dong; Jianfei Cai 001; Bohan Zhuang (ICLR, 2024)

Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers. - Xiuying Wei; Skander Moalla; Razvan Pascanu; Caglar Gulcehre (NeurIPS, 2024)

Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers. - Xiuying Wei; Skander Moalla; Razvan Pascanu; Caglar Gulcehre (CoRR, 2024)

Investigating Low-Rank Training in Transformer Language Models: Efficiency and Scaling Analysis. - Xiuying Wei; Skander Moalla; Razvan Pascanu; Caglar Gulcehre (CoRR, 2024)

AtomNet: Designing Tiny Models from Operators Under Extreme MCU Constraints. - Zhiwei Dong; Mingzhu Shen; Shihao Bai; Xiuying Wei; Jinyang Guo; Ruihao Gong; Song-Lu Chen; Xianglong Liu 001; Xu-Cheng Yin (AAAI, 2025)

From Markov to Laplace: How Mamba In-Context Learns Markov Chains. - Marco Bondaschi; Nived Rajaraman; Xiuying Wei; Kannan Ramchandran; Razvan Pascanu; Caglar Gulcehre; Michael Gastpar; Ashok Vardhan Makkuva (CoRR, 2025)

RAT: Bridging RNN Efficiency and Attention Accuracy in Language Modeling. - Xiuying Wei; Anunay Yadav; Razvan Pascanu; Caglar Gulcehre (CoRR, 2025)

Pushing the Limit of Post-Training Quantization. - Ruihao Gong; Xianglong Liu 001; Yuhang Li 001; Yunqian Fan; Xiuying Wei; Jinyang Guo (IEEE Trans. Pattern Anal. Mach. Intell., 2025)