Gain fluctuation in microwave photonic phase shifters based on stimulated Brillouin scattering. - Shaowen Peng; Zhiyao Zhang; Qihao Yang; Di Peng; Yali Zhang; Yong Liu (WOCC, 2016)

Vector Representation Based Model Considering Randomness of User Mobility for Predicting Potential Users. - Shaowen Peng; Xianzhong Xie; Tsunenori Mine; Chang Su 003 (PRIMA, 2018)

TSWNN+: Check-in Prediction Based on Deep Learning and Factorization Machine. - Chang Su 003; Ningning Liu; Xianzhong Xie; Shaowen Peng (Innovate-Data, 2019)

融合深度学习和因子分解机的兴趣点签到预测研究 (Study on Check-in Prediction Based on Deep Learning and Factorization Machine). - Chang Su 003; Shaowen Peng; Xianzhong Xie; Ningning Liu (计算机科学, 2019)

Mixture-preference bayesian matrix factorization for implicit feedback datasets. - Shaowen Peng; Tsunenori Mine (SAC, 2020)

A Robust Hierarchical Graph Convolutional Network Model for Collaborative Filtering. - Shaowen Peng; Tsunenori Mine (CoRR, 2020)

SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation. - Shaowen Peng; Kazunari Sugiyama; Tsunenori Mine (CIKM, 2022)

Less is More: Reweighting Important Spectral Graph Features for Recommendation. - Shaowen Peng; Kazunari Sugiyama; Tsunenori Mine (SIGIR, 2022)

How Powerful is Graph Filtering for Recommendation. - Shaowen Peng; Xin Liu 020; Kazunari Sugiyama; Tsunenori Mine (KDD, 2024)

Less is More: Removing Redundancy of Graph Convolutional Networks for Recommendation. - Shaowen Peng; Kazunari Sugiyama; Tsunenori Mine (ACM Trans. Inf. Syst., 2024)

UPxSocio at NTCIR-18 MedNLP-CHAT Task: Similarity-BasedFew-Shot Example Selection for Prompt-Based Detection. - Michael van Supranes; Martin Augustine B. Borlongan; Joseph Ryan G. Lansangan; Genelyn Ma. Sarte; Shaowen Peng; Shoko Wakamiya; Eiji Aramaki (NTCIR, 2025)

NAISTym at the NTCIR-18 MedNLP-CHAT: ClassifyingPatient-Chatbot Conversations with Objective and SubjectiveAssessments Using Prompting Techniques. - Lenard Paulo Velasco Tamayo; Saidah Z. Jannah; Mohamad Alnajjar; Axalia Levenchaud; Shaowen Peng; Shoko Wakamiya; Eiji Aramaki (NTCIR, 2025)

GenKP: generative knowledge prompts for enhancing large language models. - Xinbai Li; Shaowen Peng; Shuntaro Yada; Shoko Wakamiya; Eiji Aramaki (Appl. Intell., 2025)

Balancing Embedding Spectrum for Recommendation. - Shaowen Peng; Kazunari Sugiyama; Xin Liu 020; Tsunenori Mine (Trans. Recomm. Syst., 2025)