I'm Xiaolin Hu, pursuing Ph.D. at Gaoling School of Artificial Intelligence , Renmin University of China (RUC). I am fortunate to be advised by Prof. Yong Liu. Currently I am a Research Intern at Xiaomi's AI Lab , where I focus on Edge Large Language Models (LLMs), mentored by Wei Liu and Jian Luan. Previously, I received my B.E. and M.E. degrees in communication and information system from Shanghai University in 2018 and 2021, respectively. Between 2018 and 2021, I collaborated with Prof. Nicholas E. Buris as part of the Intelligent Multi-Input Multi-Output Systems (i-MIMOs) research group. Additionally, I gained research experience as an Intern at the OPPO Research Institute from October 2020 to February 2021, under the mentorship of Xianyue Wu and Tehuang Liu.

I am currently bridging LLMs and personal edge devices. With a long-term goal of contributing to a human-centered application ecosystem based on large models, I am particularly interested in: (1) Science-Driven LLMs Training: Exploring the scientific principles of LLMs training and fine-tuning. (2) Personal Edge LLMs Serving: Developing efficient algorithms for LLMs on edge devices to enhance personalized services. I won the Shanghai University President Scholarship (The highest honor among the scholarships at Shanghai University).

• Personal Pages: https://www.xiaolinhu.art (updated recently🔥)
• Linkedin: https://www.linkedin.com/in/xiaolin-hu-21429019b
• Google Scholar: https://scholar.google.com/citations?user=6CSzbVEAAAAJ&hl

• 2024.12: One paper is accepted by AAAI 2025! Stability and Generalization of Zeroth-Order Decentralized SGD with Changing Topology
• 2024.11: One paper is accepted by COLING 2025! PMSS: Pretrained Matrices Skeleton Selection for LLM Fine-tuning
• 2024.9: One paper is accepted by NeurIPS 2025! Enhancing In-Context Learning with just SVD-Based Pruning: A Theoretical Perspective
• 2024.6: Xiaomi Young Scholar Research Program (PI: Yong Liu) received approval, focusing on fine-tuning edge LLMs for personalized services.
• 2024.5: One Paper is accepted by KDD 2025! LLMs may Dominate Information Access
• 2023.12: Started internship at Xiaomi AI Lab, focusing on efficient fine-tuning of edge LLMs.

My full paper list is shown at my personal homepage.

• AAAI 2025 Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology Xiaolin Hu, Zixuan Gong, Gengze Xu, Wei Liu, Jian Luan, Bin Wang, Yong Liu, AAAI 2025

• ICLR 2023 Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses Xiaolin Hu, Shaojie Li, Yong Liu, Video

• NeurIPS 2024 Enhancing In-Context Learning with just SVD-Based Pruning: A Theoretical Perspective Xinhao Yao, Xiaolin Hu, Shenzhi Yang, Yong Liu, NeurIPS 2024

• COLING 2025 PMSS: Pretrained Matrices Skeleton Selection for LLM Fine-tuning Qibin Wang, Xiaolin Hu, Weikai Xu, Wei Liu, Jian Luan, Bin Wang, COLING 2025

• KDD 2024 Neural Retrievers are Biased Towards LLM-Generated Content Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu, Xiaolin Hu, Yong Liu, Xiao Zhang, Gang Wang, Jun Xu, KDD 2024

• APMC 2020 A Deep Learning Framework for Solving Rectangular Waveguide Problems Xiaolin Hu, Nicholas E. Buri, (Oral) |

• APMC 2019 Capacity Estimation of MIMO Systems via Support Vector Regression Xiaolin Hu, Nicholas E. Buri, (Oral)

• APMC 2020 Multiple Signal DoA Estimation with Unknown Electromagnetic Coupling using Gaussian Process Qifeng Wang, Nicholas E. Buris, Xiaolin Hu, APMC 2020

• ICIP 2021 3D Grid Transformation Network For Point Cloud Completion Xiaobao Deng, Xiaolin Hu, Nicholas E. Buris, Ping An, Yilei Chen
• Wavelength-tunable Q-switched fiber laser based on a 45 tilted fiber grating Xiaolin Hu, Zhijun Yan, Qianqian Huang, Chuanhang Zou, Tianxing Wang, Chengbo Mou, Opto-Electronic Engineering 2018