PENG SHAOWEN (SHAOWEN PENG) - マイポータル

基本情報

所属: 奈良先端科学技術大学院大学助教

研究者番号: 81002532
ORCID iD: https://orcid.org/0000-0003-4020-9100
J-GLOBAL ID: 202401010735397878
researchmap会員ID: R000065702

研究キーワード

研究分野

経歴

2024年4月 - 現在

奈良先端科学技術大学院大学

学歴

2021年4月 - 2024年3月

京都大学
2019年4月 - 2021年3月

九州大学

論文

RED: Retrieval-enhanced knowledge distillation for smaller language models

Xinbai Li, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

Expert Systems with Applications 332 133599-133599 2027年1月
Persona-Driven Data Augmentation for Disease Name Recognition Across Rare and General Disease Corpora: Comparative Evaluation Study

Jude Crener Junior Pierre, Tomohiro Nishiyama, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

JMIR Medical Informatics 2026年7月24日
Multilingual Disparities in LLM-Based Symptom Detection for Global Disease Surveillance: Findings from High- and Low-Resource Languages (Preprint)

Sa'idah Zahrotul Jannah, Tomohiro Nishiyama, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

2026年6月2日
A Multiassessment and Multiprofessional Agents Approach for Medical Chatbot Risk Estimation: Development and Evaluation Study

Lenard Paulo Velasco Tamayo, Tomohiro Nishiyama, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

JMIR Medical Informatics 2026年5月15日
Estimating Shared Mental Models via Communication-Categorized Directed Graphs

Hiroaki Tanaka, Wataru Yamada, Keiichi Ochiai, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems 1-14 2026年4月13日
Concept-Aware Learning Framework for Detecting Common Symptoms in Social Media Text: Model Development and Evaluation Study (Preprint)

Michael Van Supranes, Shaowen Peng, Tomohiro Nishiyama, Shoko Wakamiya, Eiji Aramaki

JMIR Medical Informatics 2026年3月6日
Robust Detection of Common Symptoms in Social Media Text using Concept-Aware Learning Framework (Preprint)

Michael Van Supranes, Shaowen Peng, Tomohiro Nishiyama, Shoko Wakamiya, Eiji Aramaki

2026年3月6日
Single-Agent Generation Surpasses Multi-Agent Systems in Semantic Diversity.

Cui Encheng, Shaowen Peng, Kazuhiro Ito, Jinsha Xu, Shohei Hisada, Shoko Wakamiya, Eiji Aramaki

ACL (Findings) 37993-38008 2026年
Balancing Embedding Spectrum for Recommendation

Shaowen Peng, Kazunari Sugiyama, Xin Liu, Tsunenori Mine

ACM Transactions on Recommender Systems 3(4) 56-25 2025年12月31日
Abbreviation Expansion Using a Single Word as Context.

Jude Crener Junior Pierre, Gabriel Herman Bernardim Andrade, Shaowen Peng, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

Studies in health technology and informatics 329 1814-1815 2025年8月7日
Toward Diversified Graph Recommendation via Semantic and Topology Augmentation With LLMs.

Zachary Samson Pangan, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

IEEE Access 13 205957-205977 2025年
Enhancing Hate Speech Classifiers through a Gradient-assisted Counterfactual Text Generation Strategy

Michael Van Supranes, Shaowen Peng, Shoko Wakamiya, Eiji Aramaki

Findings of the Association for Computational Linguistics: EMNLP 2025 3529-3544 2025年
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

Proceedings of the 18th NTCIR Conference on Evaluation of Information Access Technologies(NTCIR) 2025年
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

Proceedings of the 18th NTCIR Conference on Evaluation of Information Access Technologies(NTCIR) 2025年
GenKP: generative knowledge prompts for enhancing large language models

Li, X., Peng, S., Yada, S., Wakamiya, S., Aramaki, E.

Applied Intelligence 55(6) 464-464 2025年
How Powerful is Graph Filtering for Recommendation

Shaowen Peng, Xin Liu, Kazunari Sugiyama, Tsunenori Mine

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2388-2399 2024年8月24日
Less is More: Removing Redundancy of Graph Convolutional Networks for Recommendation

Peng, S., Sugiyama, K., Mine, T.

ACM Transactions on Information Systems 42(3) 85-26 2024年5月31日
Less is More: Reweighting Important Spectral Graph Features for Recommendation.

Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR) 1273-1282 2022年
SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation.

Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

Proceedings of the 31st ACM International Conference on Information & Knowledge Management(CIKM) 1625-1634 2022年
Mixture-preference bayesian matrix factorization for implicit feedback datasets.

Shaowen Peng, Tsunenori Mine

SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing(SAC) 1427-1434 2020年

もっとみる

MISC

A Robust Hierarchical Graph Convolutional Network Model for Collaborative Filtering

Shaowen Peng, Tsunenori Mine

2020年4月30日

共同研究・競争的資金等の研究課題

温故知新：古典的推薦アルゴリズムと最先端LLMの融合

日本学術振興会科学研究費助成事業若手研究 2025年4月 - 2028年3月

PENG SHAOWEN

PENG SHAOWEN

基本情報

研究キーワード

研究分野

経歴

学歴

論文

MISC

共同研究・競争的資金等の研究課題

メニュー

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