Teach LLMs to Personalize - An Approach inspired by Writing Education. - Cheng Li 012; Mingyang Zhang 001; Qiaozhu Mei; Yaqing Wang 007; Spurthi Amba Hombaiah; Yi Liang; Michael Bendersky (CoRR, 2023)

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. - Lu Yin 006; You Wu 001; Zhenyu Zhang 015; Cheng-Yu Hsieh; Yaqing Wang 007; Yiling Jia; Mykola Pechenizkiy; Yi Liang; Zhangyang Wang; Shiwei Liu 003 (CoRR, 2023)

Automated Evaluation of Personalized Text Generation using Large Language Models. - Yaqing Wang 007; Jiepu Jiang; Mingyang Zhang 001; Cheng Li 012; Yi Liang; Qiaozhu Mei; Michael Bendersky (CoRR, 2023)

Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling. - Yaqing Wang 007; Jialin Wu; Tanmaya Dabral; Jiageng Zhang; Geoff Brown; Chun-Ta Lu; Frederick Liu; Yi Liang; Bo Pang 001; Michael Bendersky; Radu Soricut (CoRR, 2023)

Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-Rank Experts. - Jialin Wu; Xia Hu; Yaqing Wang 007; Bo Pang 001; Radu Soricut (CVPR, 2024)

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. - Lu Yin 006; You Wu 001; Zhenyu Zhang 015; Cheng-Yu Hsieh; Yaqing Wang 007; Yiling Jia; Gen Li 012; Ajay Kumar Jaiswal; Mykola Pechenizkiy; Yi Liang; Michael Bendersky; Zhangyang Wang; et al. (ICML, 2024)