Updated on 2025/10/29

写真a

 
INOSHITA Keito
 
Organization
Graduate School of Business and Commerce Business and Commerce Major
External link

Degree

  • Master's Degree (Data Science) ( 2025.3   Shiga University )

Research Interests

  • Bias Detection

  • Deep Learning

  • Data Mining

  • Machine Learning

  • Sentiment Analysis

  • Natural Language Processing

  • Large Language Model

Research Areas

  • Informatics / Statistical science

  • Informatics / Computer system

  • Informatics / Information security

  • Informatics / Intelligent informatics

  • Informatics / Kansei informatics

Education

  • Shiga University   Graduate School of Data Science

    2023.4 - 2025.3

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    Country: Japan

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  • Sapporo University   School of Society and Collaboration   Business Administration major

    2020.4 - 2023.3

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    Country: Japan

    Notes: Dropped out at the end of the third year to skip to graduate school

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  • Kansai University

    2025.4

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Research History

  • 日本セーフティソサイエティ研究センター   研究員

    2025.4

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  • 国立研究開発法人科学技術振興機構 (JST) 次世代研究者挑戦的研究プログラム (SPRING) 関西大学SPRINGスカラシップ研究学生

    2025.4

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  • Shiga University

    2025.4

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Professional Memberships

  • 日本感性工学会

    2025.6 - Present

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  • 情報知識学会

    2025.3 - Present

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  • 言語処理学会

    2025.2 - Present

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  • 日本データベース学会

    2025.2 - Present

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  • 日本情動学会

    2025.2 - Present

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  • 人工知能学会

    2025 - Present

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  • ACL (Association for Computational Linguistics)

    2024 - Present

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  • IEEE Computer Society

    2023 - Present

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  • 情報処理学会

    2023 - Present

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Committee Memberships

  •   IEEE Kansai Section Young Professionals Affinity Group - Member  

    2025.4 - Present   

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  •   International Conference on Natural Language Processing for Digital Humanities (NLP4DH) - Program Committee  

    2025.1 - Present   

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    Committee type:Academic society

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  •   IEEE Kansai Section Young Professionals Affinity Group - Associate  

    2024.10 - 2025.4   

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Papers

  • Reproducing Developmental Features and Preserving Semantics in Child-Style Text Generation Using LLM Reviewed

    Keito Inoshita, Rushia Harada, Keisuke Motomura

    Proceedings of the IEEE 14th Global Conference on Consumer Electronics (IEEE GCCE)   2025.9

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  • GNN-Enhanced Multimodal Fusion with Contrastive Learning for Smart Health Oriented High Performance Recommendation System Reviewed

    Ryutaro Matsuoka, Keito Inoshita, Xiaokang Zhou, Zhigao Zheng, Akira Kawai, Katsutoshi Yada

    Proceedings of the 2025 IEEE International Conference on High Performance Computing and Communications (IEEE HPCC)   864 - 871   2025.8

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  • Enhancing Sentiment Analysis Accuracy and Evaluating Task Affinity Using Large Language Models Reviewed

    Keito Inoshita

    Proceedings of the 2025 IEEE International Conference on Artificial Intelligence for Learning and Optimization (IEEE ICoAILO)   181 - 187   2025.8

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)  

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  • Evaluation of the Automated Labeling Method for Taxonomic Nomenclature Through Prompt-Optimized Large Language Model Reviewed

    Keito Inoshita, Kota Nojiri, Haruto Sugeno, Takumi Taga

    Proceedings of the 2025 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IEEE IAICT)   528 - 535   2025.7

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  • Persona-Based Synthetic Data Generation Using Multi-Stage Conditioning with Large Language Models for Emotion Recognition

    Keito Inoshita, Rushia Harada

    arXiv   2025.7

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  • Role-Playing LLM-Based Multi-Agent Support Framework for Detecting and Addressing Family Communication Bias Reviewed

    Rushia Harada, Yuken Kimura, Keito Inoshita

    Proceedings of The 1st International Workshop on AI-empowered Digital Health and Well-being Promotion (AI-DHWP @ CyberSciTech 2025) (to appear)   2025.7

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    Authorship:Corresponding author  

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  • Multi-Scale Convolutional Fusion with Contrastive Feature Alignment for Imbalanced Data Classification Reviewed

    Keito Inoshita Takato Ueno, Xiaokang Zhou

    Proceedings of the 30th International Conference on Natural Language & Information Systems (NLDB)   ( 15836 )   2025.7

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)  

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  • Dual-Branch Feature Extraction via Discrepancy-Aware Fusion with Evidential Deep Learning for Sarcasm Detection Reviewed

    Takato Ueno, Keito Inoshita

    Proceedings of the 2025 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IEEE IAICT)   345 - 352   2025.7

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    Authorship:Corresponding author  

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  • A Multi-Agent Probabilistic Inference Framework Inspired by Kairanban-Style CoT System with IdoBata Conversation for Debiasing Reviewed

    Takato Ueno, Keito Inoshita

    Proceedings of the 23rd International Conference on Pervasive Intelligence and Computing (IEEE PICom) (to appear)   2025.6

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  • Introducing Large Language Models to Human-Based Etymological Classification in Zooplankton

    Haruto Sugeno, Keito Inoshita, Kota Nojiri, Takumi Taga

    bioRxiv   2025.5

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  • Automated Labeling of Scientific Names and Etymological Trend Analysis in Phytophagous Arthropods Using Large Language Model Reviewed

    Kota Nojiri, Keito Inoshita, Haruto Sugeno

    Zoological Science   2025.3

  • Multi-Stage Evolutionary Model Merging with Meta Data Driven Curriculum Learning for Sentiment-Specialized Large Language Modeling Reviewed

    Keito Inoshita, Xiaokang Zhou, Akira Kawai

    Proceedings of the 10th IEEE International Conference on Data Science and Systems (IEEE DSS)   58 - 65   2024.12

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)  

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  • Bias Examination of International Conflict Structures in Large Language Models and Debiasing Methods Based on Active and Passive Approaches Reviewed

    Keito Inoshita

    じんもんこん2024論文集   2024.12

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  • Evolutionary Expert Model Merging with Task-Adaptive Iterative Self-Improvement Process for Large Language Modeling on Aspect-Based Sentiment Analysis Reviewed

    Keito Inoshita

    Proceedings of the 2024 IEEE International Conference on Internet of Things and Intelligence Systems (IEEE IoTaIS)   130 - 136   2024.11

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iotais64014.2024.10799461

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  • Multifaceted Exploration of Perceptions on the Ukraine-Russia War in the Japanese Twitter Space Reviewed

    Keito Inoshita

    Proceedings of the 2024 IEEE International Conference on Internet of Things and Intelligence Systems (IEEE IoTaIS)   58 - 64   2024.11

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iotais64014.2024.10799391

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  • Quantitative Analysis of Political Party Understanding and the Impact of Political Bias through ChatGPT Reviewed

    Keito Inoshita

    SHS Web of Conferences   204   03012 - 03012   2024.11

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (scientific journal)   Publisher:EDP Sciences  

    In recent years, large language models (LLMs) such as ChatGPT have been utilized for acquiring political knowledge. However, there remain questions about their accuracy and fairness, as these models may harbour biases in understanding political parties. This study aims to quantify the understanding of Japanese political parties using the ChatGPT model and evaluate the model’s biases and their impacts. Specifically, we conducted experiments using pairs of questions and answers that reflect the stances of each party to investigate the extent to which the model demonstrates understanding toward specific parties. The experimental results revealed that ChatGPT-4 exhibits a significantly higher level of understanding towards the Liberal Democratic Party, while its understanding of newer parties like Reiwa Shinsengumi is lower. Additionally, the GPT model acting as a voter tends to have a positive bias towards certain parties and reflects progressive ideologies. It was also shown that the recognition of political parties influences the model’s understanding, with factors such as the number of seats, advertising expenses, and the frequency of party names in the dataset potentially playing crucial roles. Based on these findings, this study provides a foundation for enhancing the accuracy and fairness of party understanding using GPT models and proposes improvements for future research and practice.

    DOI: 10.1051/shsconf/202420403012

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  • Assessing GPT's Legal Knowledge in Japanese Real Estate Transactions Exam Reviewed

    Keito Inoshita

    Proceedings of the 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)   149 - 155   2024.11

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/3ict64318.2024.10824669

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  • Sentiment Bias and Security Analysis in Training Datasets of Large Language Models Reviewed

    Keito Inoshita, Xiaokang Zhou

    Proceedings of the 14th IEEE International Conference on Big Data and Cloud Computing (IEEE BDCloud)   1 - 8   2024.11

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  • Corpus Development Based on Conflict Structures in the Security Field and LLM Bias Verification Reviewed

    Keito Inoshita

    Proceedings of the 4th International Conference on Natural Language Processing for Digital Humanities   504 - 512   2024.11

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:Association for Computational Linguistics  

    DOI: 10.18653/v1/2024.nlp4dh-1.49

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  • The Efficient Development of Conflict Structure Datasets for Evaluating Sentiment Recognition Bias in Large Language Models Reviewed

    Keito Inoshita

    Proceedings of the 2024 International Conference on Electrical Engineering and Informatics (ICELTICs)   7 - 12   2024.9

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iceltics62730.2024.10776050

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  • Sentiment Analysis of Japanese Twitter Users Regarding the Ukraine-Russia War and Its Implications for Security Policy Reviewed

    Keito Inoshita

    Proceedings of the 11th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)   338 - 343   2024.8

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/icitacee62763.2024.10762783

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  • Multi-Domain and Multi-View Oriented Deep Neural Network for Sentiment Analysis in Large Language Models Reviewed

    Keito Inoshita, Xiaokang Zhou, Shohei Shimizu

    Proceedings of the 2024 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics   149 - 156   2024.8

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/ithings-greencom-cpscom-smartdata-cybermatics62450.2024.00045

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  • Assessment of Conflict Structure Recognition and Bias Impact in Japanese LLMs Reviewed

    Keito Inoshita

    Proceedings of the 5th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON)   1 - 5   2024.6

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/times-icon61890.2024.10630720

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MISC

  • 知識駆動のドメイン調整と多様性の拡張に基づく大規模言語モデルを活用した感情データ生成

    井下敬翔

    第22回テキストアナリティクス・シンポジウム   2025.9

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  • Can a large language model generate writing styles across ages

    2025.9

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  • 属人性を排除した大規模言語モデルによる感情データ生成

    井下敬翔

    第20回言語処理若手シンポジウム(YANS)   2025.9

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  • Persona-Enhanced Emotion Text Generation with Large Language Models

    2025.9

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  • Assessing and Mitigating Language Models’ Classification Performance on Children’s Text

    Keito Inoshita, Yuken Kimura

    2025.9

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  • 学名が語る恣意性:語源に潜むバイアスの構造を可視化する

    野尻康太, 井下敬翔, 菅野遥登, 多賀匠

    日本動物学会 第96回名古屋大会   2025.9

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  • 自然言語処理による感情認識技術の研究動向と今後の課題

    原佑太郎, 井下敬翔

    第264回自然言語処理研究発表会   2025.7

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  • 大規模言語モデルの政治的影響とガバナンスの指針

    井下敬翔

    第44回(R6年度)学生論文昭和池田賞   2025.6

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  • 学名の裏側をズバリ解明: 魚類と動物プランクトンの語源を大規模言語モデルで探る

    菅野遥登, 井下敬翔, 野尻康太, 多賀匠

    2025年度中国四国地区生物系三学会合同大会愛媛大会   2025.5

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    Publishing type:Research paper, summary (national, other academic conference)  

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  • 回覧板と井戸端会議に着想を得たマルチエージェント確率的 推論フレームワークの検証

    上野孝斗, 井下敬翔

    研究報告人文科学とコンピュータ(CH) 2024-CH-136   2025.5

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  • 京都・滋賀・奈良3府県の観光拠点間における口コミの類似性に着目した観光候補地群の分析

    尾﨑博信, 井下敬翔

    情報知識学会誌   35 ( 2 )   327 - 333   2025.5

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  • 大規模言語モデル (LLM) を用いた学名の語源分類と命名傾向の時系列変化

    野尻康太, 井下敬翔, 菅野遥登

    2025年度中国四国地区生物系三学会合同大会愛媛大会   2025.5

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  • 職場環境におけるマルチモーダル感情認識技術の現状と展望

    井下敬翔, 尾崎博信

    情報知識学会誌   35 ( 2 )   151 - 156   2025.5

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  • スポーツ長官賞: スポーツの小型化とモジュール型小規模競技場によるウェルビーイングな都市デザイン Invited

    井下敬翔

    社会教育   44 ( 45 )   2025.3

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  • 感情データが導く生成AI時代のWell-beingな職場環境

    井下敬翔

    第25回理工学系学生科学技術論文コンクール入賞論文集   2025.3

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  • 視点の改革:中国に対するバイアスを超えて

    井下敬翔

    人民中国   2025.1

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    Authorship:Lead author   Publishing type:Book review, literature introduction, etc.  

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  • Enhancing Workplace Well-being Through Generative AI-Driven Emotion Analysis Invited

    Keito Inoshita

    Globe, Universe, Next future, Discussions And Mentions   1 ( 2 )   109 - 114   2025.1

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  • パラリンピックが教えてくれた「本当の強さ」

    井下敬翔

    雑誌 「リハビリテーション」   2025

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  • パーソナル AI と組織 AI による ⼈事管理の⾰新と最適化

    井下敬翔

    人と仕事の未来研究所第1回懸賞論文   2024.12

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  • スポーツの小型化とモジュール型小規模競技場によるウェルビーイングな都市デザイン, Invited

    井下敬翔

    月刊体育施設   ( 12月 )   43 - 44   2024.12

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  • ベイズ深層学習とLLMを活用した公衆衛生基準に基づくトコジラミ分布予測サービスの提案

    井下敬翔

    2024.11

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  • 核兵器に頼る国のリーダーへ:リアリズムと革新による平和への道

    井下敬翔

    「核なき未来」オピニオン   2024.8

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  • A Novel Dataset Development Method for Evaluating Sentiment Recognition Bias of Large Language Models in Conflict Structures

    Keito Inoshita

    研究報告人文科学とコンピュータ(CH)   2024-CH-136 ( 2 )   1 - 4   2024.6

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  • 日本語Twitter空間における戦争認識の多角的探索 :ウクライナ-ロシア戦争への反応と洞察

    井下敬翔

    研究報告人文科学とコンピュータ(CH)   2024-CH-135 ( 1 )   1 - 8   2024.5

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Presentations

  • 人間の感情データを大規模言語モデルで作ってみた

    井下敬翔

    関西大学第 4 回院生合同学術研究ポスター発表大会 2025  2025.10 

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  • 自律的なAI間対話による人間中心のフィードバックとWell-Being支援

    井下敬翔

    SIAI #7 産学クロススクエア 「ミライをつくるAI人材」ポスター発表  2025.9 

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  • 大規模言語モデルを活用した感情データの自給自足

    井下敬翔

    日本財団HUMAIプログラムポスター発表会  2025.9 

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  • 文脈に配慮したLLMベースの感情認識技術

    井下敬翔

    SIAI #7 産学クロススクエア 「ミライをつくるAI人材」ポスター発表  2025.9 

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  • LLMを活用した属人性のない人間らしいデータ生成

    井下敬翔

    SIAI #7 産学クロススクエア 「ミライをつくるAI人材」ポスター発表  2025.9 

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  • 感情データを人間から取得する必要がない未来の話

    井下敬翔

    第1回グローバル・アントレプレナーシップ・フォーラム  2025.8 

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  • ペルソナを活用した大規模言語モデルによる感情テキスト生成

    井下敬翔

    2025年度戸部眞紀財団交流会研究発表会  2025.8 

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  • LLMで感情を作る

    井下敬翔

    NLP Dの会  2025.7 

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  • 価値を生み出す学びと実績のサイクル

    井下敬翔

    滋賀大学サステナウィーク  2024.11 

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Awards

  • 優秀賞 - 関西大学第 4 回院生合同学術研究ポスター発表大会

    2025.10  

    井下敬翔

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  • 支部大会奨励賞 - 2025年度 情報処理学会関西支部 支部大会

    2025.9  

    井下敬翔

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  • Best Paper Award - the 2025 IEEE International Conference on Artificial Intelligence for Learning and Optimization (IEEE ICoAILO)

    2025.8  

    Keito Inoshita

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  • Best Paper Award - The 2025 IEEE International Conference on High Performance Computing and Communications (IEEE HPCC)

    2025.8  

    Ryutaro Matsuoka, Keito Inoshita, Xiaokang Zhou, Zhigao Zheng, Akira Kawai, Katsutoshi Yada

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  • Best Paper Award - The 30th International Conference on Natural Language & Information Systems (NLDB 2025)

    2025.7  

    Keito Inoshita, Takato Ueno, Xiaokang Zhou

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  • 奨励賞-ISUZU AI Innovation Challenge 2024

    2025.6  

    井下敬翔

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  • 特別奨励賞-第44回(R6年度)学生論文昭和池田賞

    2025.6  

    井下敬翔

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  • 入賞-第25回理工系学生科学技術論文コンクール

    2025.3  

    井下敬翔

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  • AI賞 - LOD チャレンジ2024

    2024.12  

    井下敬翔

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  • Best Paper Award - the 10th IEEE International Conference on Data Science and Systems (IEEE DSS)

    2024.12  

    Keito Inoshita, Xiaokang Zhou, Akira Kawai

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  • 奨励賞 - 人と仕事の未来研究所第1回懸賞論文

    2024.11  

    井下敬翔

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  • Best Paper Award - the 2024 IEEE International Conference on Internet of Things and Intelligence System (IEEE IoTaIS)

    2024.11  

    Keito Inoshita

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  • Best Paper Award - the 14th IEEE International Conference on Big Data and Cloud Computing (IEEE BDCloud)

    2024.10  

    Keito Inoshita, Xiaokang Zhou

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  • 3位 - The IEEE R10 Ethics and Enterprise Risk Management committee Student Contest

    2024.9  

    Keito inoshita

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  • Best Paper Award - International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE 2024)

    2024.8  

    Keito Inoshita

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  • Excellent Supporter Award - IEEE CyberSciTech/DASC/PICom/CBDCom 2025

    2025.10  

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  • 第2位 - 第3回鉄道150年記念障害福祉賞

    2025.9  

    井下敬翔

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  • 優秀賞&協賛企業賞-関西大学SFinX

    2025.8  

    井下敬翔

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  • 採択 - ~未踏的な地方の若手人材発掘育成事業~LEADING EDGE 四国

    2025.8  

    井下敬翔

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  • 審査員特別賞-武蔵大学ビジネスプランコンテスト

    2025.2  

    井下敬翔

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  • 学長賞-滋賀大学

    2025.2  

    井下敬翔

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  • KINTO未来ファンド賞

    2025.1  

    井下敬翔

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  • 優秀賞 - 第2回西播磨ビジネスコンテスト

    2024.12  

    井下敬翔

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  • 入賞 - 「大学生」空き家活用アイデアコンテスト

    2024.11  

    井下敬翔

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  • 優秀賞 - 夢をつくるプロジェクト2024

    2024.11  

    井下敬翔

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  • 「しま」のビジネスチャレンジ賞 - ながさき「しま」のビジネスチャレンジ

    2024.11  

    井下敬翔

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  • スポーツ庁長官賞 - スポーツ・健康まちづくりデザイン学生コンペティション2024

    2024.11  

    井下敬翔

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  • 環境大臣賞 - APEV: 「モビリティで2030を創る」国際ワークショップ

    2024.11  

    井下敬翔, HAL名古屋メンバー

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  • エシカル・データ賞 - 岡山ガス ビジネスプランコンテスト2024

    2024.11  

    井下敬翔

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  • 採択 - 学生 ACTION CAMP 2024

    2024.10  

    井下敬翔

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  • 優秀賞 - Panda杯全日本青年作文コンクール2024

    2024.10  

    井下敬翔

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  • 優秀賞 - 関西大学ビジネスプラン・コンペティション(KUBIC)

    2024.10  

    井下敬翔

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  • 最優秀賞 - NEC Analytics Challenge Cup for Business Idea 2024

    2024.10  

    井下敬翔 曽我美結

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  • 入賞 - 第5回創生アイデアコンテストA部門

    2024.9  

    井下敬翔

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  • 最優秀賞&テーマ賞 - Electric Sheepアイデアコンテスト2024

    2024.9  

    井下敬翔

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  • 採択 - 水地域イノベーション財団 2024年度支援事業ビジネスプランコンテスト

    2024.9  

    井下敬翔

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  • 敢闘賞 - 第9回芝浦ビジネスモデルコンペティション

    2024.9  

    井下敬翔

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  • 優秀賞 - 第2回高速道路DXアイデアコンテストアイデア部門

    2024.6  

    井下敬翔

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Research Projects

  • 感情データの自給自足による自己進化型感情認識AIの構築

    2025.8 - 2026.3

    日本財団  HUMAIプログラム 奨励金B 

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  • 生成AIによる倫理・法的制約を受けない感情データ生成及び、誰もが安心して使えるWell-being支援プラットフォーム

    2025.8 - 2026.1

    ~未踏的な地方の若手人材発掘育成事業~LEADING EDGE 四国 

    井下敬翔

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  • 職場環境の Well-being 向上を実現する 対話型マルチモーダル感情認識システムの構築

    2025.4 - 2028.3

    国立研究開発法人科学技術振興機構(JST)「次世代研究者挑戦的研究プログラム ~博士後期課程学生の挑戦を支援する~」 

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  • 職場環境におけるマルチモーダルLLMを用いた感情シミュレーション&ゲーミングによる意思決定支援と組織学習の強化

    2025.4 - 2026.3

    公益財団法人 科学技術融合振興財団  調査研究補助金 

    井下敬翔

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    Authorship:Principal investigator 

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Other

  • 公益財団法人地域育成財団奨学生

    2025.10 - Present

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  • 日本学生支援機構大学院第一種奨学金業績優秀者 (全額免除)

    2025.7

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  • 関西大学給付奨学金

    2025.6

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  • 公益財団法人戸部眞紀財団奨学生

    2025.4 - Present

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  • 公益財団法人鴻池奨学財団奨学生

    2025.4 - 2028.3

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  • 滋賀大学データサイエンス研究科奨学金

    2024.4

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  • 保持資格

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    統計検定準1級,
    基本情報技術者,
    宅地建物取引士,
    データサイエンス発展

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  • 修了証-AI経営講座(AI Business Insights 2025)

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Social Activities

  • スポーツによる健康、まちづくりについて玉野市へプレゼン

    Role(s): Appearance, Informant

    スポーツ庁  スポーツ•健康まちづくりデザイン学生コンペティション  2025.2

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    Type:Lecture

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Academic Activities

  • Reviewer (Annual Conference on Neural Information Processing Systems)

    Role(s): Peer review

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  • Reviewer (後日公開)

    Role(s): Peer review

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  • Reviewer (Natural Language Processing for Digital Humanities)

    Role(s): Peer review

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  • Reviewer (IEEE Transactions on Affective Computing)

    Role(s): Peer review

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  • Reviewer (日本認知科学会)

    Role(s): Peer review

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