Masanori HIRANO

1. Honorable Mention Award in 16th IIAI International Congress on Advanced Applied Informatics (07/2024)
2. Dean’s Award AY2023, School of Engineering, The University of Tokyo (03/2024)
   University Press
3. Best Paper Award (2023), The Japanese Institute of Electronics, Information and Communication Engineers (IEICE) Research Group on Language Understanding and Communication (NLC) (02/2024)Official HP
4. AY2022 Student Best Paper Award, Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (10/2023)Official HP
5. IEEE Computer Society Japan Chapter JAWS Young Researcher Award (09/2023) Official HP
6. JAWS (Joint Agent Workshop & Symposium) Excellence Award (09/2023) Official HP
7. Young Research Award, Special Interest Group on Natural Language Processing (SIG-NL) Information Processing Society of Japan (IPSJ) (09/2023) Official HP
8. Honorable Mention Award, 18th Symposium of Young Researcher Association for NLP Studies (Yans) (08/2023) Official HP
9. ELYZA Award (Sponsor Award), 18th Symposium of Young Researcher Association for NLP Studies (Yans) (08/2023) Official HP
10. Competitive Paper Award in 14th IIAI International Congress on Advanced Applied Informatics (07/2023)
11. Competitive Paper Award in 13th IIAI International Congress on Advanced Applied Informatics (12/2022)
12. Best paper award in the 6th IEEE International Conference on Agents (IEEE ICA 2022) (11/2022)
13. Student best paper award in the 9th International Conference on Behavioral and Social Computing (BESC 2022) (10/2022) Official HP
14. Runner-up award in the 6th Symposium on Multi Agent Systems for Harmonization (SMASH22 Summer Symposium) (09/2022) Official HP
15. Encouragement award in the 6th Symposium on Multi Agent Systems for Harmonization (SMASH22 Summer Symposium) (09/2022) Official HP
16. Best Paper Award in 12th IIAI International Congress on Advanced Applied Informatics (07/2022)
    University Press / University Press 2
17. The Japanese Society for Artificial Intelligence (JSAI) Incentive Award (AY 2021)
    Introduction (Japanese Only)
18. The Japanese Society for Artificial Intelligence (JSAI) Annual Conference Excellence Award (2021)
    Introduction (Japanese Only) / University Press / University Press 2
19. Dean’s Award AY2020, School of Engineering, The University of Tokyo (03/2021)
    University Press (Japanese Only) / University Press 2
20. Nominated for student paper award in the 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2020) (11/19/2020) Official HP
21. Nominated for best paper award in the 22nd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2019) (10/30/2019) Official HP
22. Winner (1st place) of Collusion Track in Supply Chain Management League (SCML) of the Tenth International Automated Negotiating Agents Competition (ANAC 2019) (08/15/2019) Official HP / University Press / University Press 2
23. Winner (1st place) of Standard Track in Supply Chain Management League (SCML) of the Tenth International Automated Negotiating Agents Competition (ANAC 2019) (08/15/2019) Official HP / University Press / University Press 2
24. Dean’s Award AY2018, Faculty of Engineering, The University of Tokyo (03/2019)
    
25. The Japanese Society for Artificial Intelligence (JSAI) Annual Conference Student Incentive Award (2018)
    Introduction (Japanese Only) / University Press / University Press 2 (Japanese Only)

1. Long Cheng, Kiyoshi Izumi, Masanori Hirano ,
   “Improvement and Analysis of Peak Shift Demand Response Scenarios of Industrial Consumers Using an Electricity Market Model,”
   New Generation Computing, 2024.
   doi.org/10.1007/s00354-024-00282-1, detail
2. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,
   “PGSGAN: Policy Gradient Stock GAN,”
   International Journal of Smart Computing and Artificial Intelligence, vol.8, no.2, p.IJSCAI832, 2024.
   doi.org/10.52731/ijscai.v8.i1.832, detail
3. Masahiro Suzuki, Hiroki Sakaji, Masanori Hirano, Kiyoshi Izumi,
   “FinDeBERTaV2: Word-Segmentation-Free Pre-trained Language Model for Finance,” [in Japanese]
   Transactions of the Japanese Society for Artificial Intelligence, vol.39, no.4, p.FIN23-G_1-14, 2024.
   doi.org/10.1527/tjsai.39-4_FIN23-G, detail
4. Long CHENG, Masanori HIRANO, Kiyoshi IZUMI,
   “Analysis of Carbon Neutrality Strategies of Industrial Consumers Using Electric Power Market Simulations,” [in Japanese]
   Journal of Information Processing, vol.65, no.1, pp.46-60, 2024.
   doi.org/10.20729/00231730, detail
5. Masanori HIRANO, Ryo WAKASUGI, Kiyoshi IZUMI,
   “Scenario Analysis of Demand Response Using Artificial Electric Power Market Simulations,”
   International Journal of Service and Knowledge Management, vol.7, no.2, p.IJSKM770, 2023.
   doi.org/10.52731/ijskm.v7.i2.770, detail
6. Masanori HIRANO, Kiyoshi IZUMI,
   “Neural-network-based Parameter Tuning for Multi-agent Simulation using Deep Reinforcement Learning,”
   World Wide Web, vol.26, no.5, 2023.
   doi.org/10.1007/s11280-023-01197-5, detail
   Impact Factor: 3.7 (2022). Q1 Journal as of 2023.
7. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
   “Constructing and Analyzing Domain-Specific Language Model for Financial Text Mining,”
   Information Processing & Management, vol.60, no.2, e103194, 2023.
   doi.org/10.1016/j.ipm.2022.103194, detail
   Impact Factor: 7.466, Q1 Journal as of 2022
8. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,
   “STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets using Residual Blocks or Transformers,”
   New Generation Computing Optional, Springer, vol.40, no.1, pp.7-24, 2022.
   doi.org/10.1007/s00354-021-00145-z, detail
9. Masanori HIRANO, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Hiroki SAKAJI,
   “Comparing Actual and Simulated HFT Traders' Behavior for Agent Design,”
   Journal of Artificial Societies and Social Simulation, University of Surry, vol.23, no.6, e6, 2020.
   doi.org/10.18564/jasss.4304, detail
   (Q1 Journal as of 2020)
10. Masanori HIRANO, Kiyoshi IZUMI, Takashi SHIMADA, Hiroyasu MATSUSHIMA, Hiroki SAKAJI,
    “Impact Analysis of Financial Regulation on Multi Assets Markets using Artificial Market Simulations,”
    Journal of Risk and Financial Management, MDPI, vol.13, no.4, e75, 2020.
    doi.org/10.3390/jrfm13040075, detail
11. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Related Stocks Selection with Data Collaboration Using Text Mining,”
    Information (ISSN 2078-2489), MDPI, vol.10, no.3, e102, 2019.
    doi.org/10.3390/info10030102, detail

1. Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta,
   “A Multi-agent Market Model Can Explain the Impact of AI Traders in Financial Markets -- A New Microfoundations of GARCH model,”
   The 25th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2024), Kyoto, Japan, Nov. 18th, 2024.
   detail
   arXiv:2409.12516 (doi.org/10.48550/arXiv.2409.12516)
2. Masanori Hirano,
   “Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Assets Simulators,”
   IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr 2024), Hoboken, NJ, USA, Oct. 22nd, 2024.
   detail
3. Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano,
   “Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study,”
   15th International Conference on Smart Computing and Artificial Intelligence (SCAI 2024) in 16th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2024), pp.329-336, July 7th, 2024.
   doi.org/10.1109/IIAI-AAI63651.2024.00068, detail
   arXiv:2311.07231 (doi.org/10.48550/arXiv.2311.07231), ssrn.com/abstract=4630864 (doi.org/10.2139/ssrn.4630864)
   Accept rate (Full paper): 87 / 293 = 29.7%
4. Masanori Hirano, Kentaro Imajo,
   “Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training,”
   15th International Conference on Smart Computing and Artificial Intelligence (SCAI 2024) in 16th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2024), pp.273-279, July 6th, 2024.
   doi.org/10.1109/IIAI-AAI63651.2024.00059, detail
   arXiv:2404.10555 (doi.org/10.48550/arXiv.2404.10555), ssrn.com/abstract=4796245 (doi.org/10.2139/ssrn.4796245)
   Accept rate (Full paper): 87 / 293 = 29.7%, Honorable mention award!
5. Masanori Hirano,
   “Construction of a Japanese Financial Benchmark for Large Language Models,”
   Joint Workshop of the 7th Financial Technology and Natural Language Processing (FinNLP), the 5th Knowledge Discovery from Unstructured Data in Financial Services (KDF), and The 4th Workshop on Economics and Natural Language Processing (ECONLP) in conjunction with LREC-COLING-2024, pp.1-9, Torino, Italy, May 20th, 2024.
   aclanthology.org/2024.finnlp-1.1, detail
   arXiv:2403.15062 (doi.org/10.48550/arXiv.2403.15062), ssrn.com/abstract=4769124 (doi.org/10.2139/ssrn.4769124)
6. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
   “From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models,”
   2023 IEEE International Conference on Big Data (IEEE BigData 2023), pp.5684-5693, Sorrento, Italy, Dec. 15th, 2023.
   doi.org/10.1109/BigData59044.2023.10386605, detail
   arXiv:2309.03412 (doi.org/10.48550/arXiv.2309.03412), ssrn.com/abstract=4564308 (doi.org/10.2139/ssrn.4564308)
7. Masanori HIRANO, Kentaro MINAMI, Kentaro IMAJO,
   “Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling,”
   4th ACM International Conference on AI in Finance (ICAIF '23), pp.19-26, Brooklyn, NY, USA, Nov. 27th, 2023.
   doi.org/10.1145/3604237.3626846, detail
   arXiv:2307.13217 (doi.org/10.48550/arXiv.2307.13217), ssrn.com/abstract=4520273 (doi.org/10.2139/ssrn.4520273)
8. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
   “llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodology,”
   The 12th International Workshop on Web Services and Social Media (WSSM-2023) in The 26th International Conference on Network-Based Information Systems (NBiS-2023), pp.442-454, Chiang Mai, Thailand, Sep. 6th, 2023.
   doi.org/10.1007/978-3-031-40978-3_47, detail
   arXiv:2305.12720 (doi.org/10.48550/arXiv.2305.12720), ssrn.com/abstract=4454626 (doi.org/10.2139/ssrn.4454626)
9. Masanori HIRANO, Kiyoshi IZUMI,
   “Quantitative Evaluation of Multi-agent Simulation using Generative Adversarial Network,”
   9th International Conference on Computational Social Science (IC2S2), Copenhagen, Denmark, July 20th, 2023.
   detail
10. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,
    “Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets,”
    13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), pp.361-368, Koriyama, Japan, July 9th, 2023.
    doi.org/10.1109/IIAI-AAI59060.2023.00077, detail
    arXiv:2204.13338 (doi.org/10.48550/arXiv.2204.13338), ssrn.com/abstract=4454626 (doi.org/10.2139/ssrn.4454626)
    Accept rate (Full paper): 86 / 251 = 34%, Competitive paper award!
11. Masanori HIRANO, Kentaro IMAJO, Kentaro Minami, Takuya SHIMADA,
    “Efficient Learning of Nested Deep Hedging using Multiple Options,”
    13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), pp.514-521, Koriyama, Japan, July 9th, 2023.
    doi.org/10.1109/IIAI-AAI59060.2023.00104, detail
    arXiv:2305.12264 (doi.org/10.48550/arXiv.2305.12264), ssrn.com/abstract=4454377 (doi.org/10.2139/ssrn.4454377)
    Accept rate (Full paper): 86 / 251 = 34%
12. Masanori HIRANO, Kiyoshi IZUMI,
    “Efficient Parameter Tuning for Multi-agent Simulation Using Deep Reinforcement Learning,”
    12th International Conference on Smart Computing and Artificial Intelligence (SCAI 2022-Winter) in 13th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022 winter), pp.130-137, Phuket, Thailand, Dec. 12th, 2022.
    doi.org/10.1109/IIAI-AAI-Winter58034.2022.00035, detail
    Competitive Paper Award
13. Masanori HIRANO, Kiyoshi IZUMI,
    “Quantitative Tuning of Artificial Market Simulation using Generative Adversarial Network,”
    The 6th IEEE International Conference on Agents (ICA 2022), pp.12-17, Online, Nov. 28th, 2022.
    doi.org/10.1109/ICA55837.2022.00009, detail
    Accept rate (Oral): 6 / 17 = 35%, Best paper award
14. Masanori HIRANO, Kiyoshi IZUMI,
    “Does Order Simultaneity Affect the Data Mining Task in Financial Markets? -- Effect Analysis of Order Simultaneity using Artificial Market,”
    The 24th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2022), pp.297-313, Valencia, Spain, Nov. 17th, 2022.
    doi.org/10.1007/978-3-031-21203-1_18, detail
    Accept rate (Long paper): 31 / 100 = 31%
15. Masanori HIRANO, Ryo WAKASUGI, Kiyoshi IZUMI,
    “Analysis of Carbon Neutrality Scenarios of Industrial Consumers Using Electric Power Market Simulations,”
    The 24th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2022), pp.90-105, Valencia, Spain, Nov. 17th, 2022.
    doi.org/10.1007/978-3-031-21203-1_6, detail
    Accept rate (Long paper): 31 / 100 = 31%
16. Masanori HIRANO, Kiyoshi IZUMI,
    “Parameter Tuning Method for Multi-agent Simulation using Reinforcement Learning,”
    The 9th International Conference on Behavioral and Social Computing (BESC 2022), pp.1-7, Matsuyama, Ehime, Japan, Oct. 29th, 2022.
    doi.org/10.1109/BESC57393.2022.9995509, detail
    Accept rate (Long paper): 22 / 83 = 27%; Student best paper.
17. Masahiro SUZUMI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Constructing and Analyzing Domain-Specific Language Model for Financial Text Mining,”
    Information Processing and Management Conference, Online, Oct. 21st, 2022.
    detail
18. Masanori HIRANO, Ryo WAKASUGI, Kiyoshi IZUMI,
    “Analysis of Demand Response Scenarios by Industrial Consumers Using Artificial Electric Power Market Simulations,”
    7th International Conference on Business Management of Technology (BMOT 2022) in 12th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022), pp.547-554, Kanazawa, Japan, July 7th, 2022.
    doi.org/10.1109/IIAIAAI55812.2022.00111, detail
    Accept rate (Long paper): 80 / 239 = 33%, Best paper award!
19. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,
    “Implementation of Actual Data for Artificial Market Simulation,”
    The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS2022), pp.1624-1626, Online, May 13th, 2022.
    doi.org/10.5555/3535850.3536056, detail
    www.ifaamas.org/Proceedings/aamas2022/pdfs/p1624.pdf
20. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,
    “Concept and Practice of Artificial Market Data Mining Platform,”
    2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), pp.1-10, Online, May 5th, 2022.
    doi.org/10.1109/CIFEr52523.2022.9776095, detail
21. Rei TAGUCHI, Hikaru WATANABE, Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI, Kiyoshi IZUMI, Kenji HIRAMATSU,
    “Market Trend Analysis Using Polarity Index Generated from Analyst Reports,”
    The 4th International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC2021) in conjunction with 2021 IEEE International Conference on Big Data (Big Data), pp.3486-3494, Online, Dec. 15th, 2021.
    doi.org/10.1109/BigData52589.2021.9671702, detail
22. Masanori HIRANO, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI, Hiroki SAKAJI,
    “STBM: Stochastic Trading Behavior Model for Financial Markets,”
    Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2020), Advances in Artificial Intelligence, vol.1357, pp.157-165, 2021.
    doi.org/10.1007/978-3-030-73113-7_14, detail
23. Masanori HIRANO, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI, Hiroki SAKAJI,
    “Implementation of Real Data for Financial Market Simulation using Clustering, Deep Learning, and Artificial Financial Market,”
    The 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2020), pp.3-18, Online, Nov. 19th, 2020.
    doi.org/10.1007/978-3-030-69322-0_1, detail
    Accept rate (Full paper): 19 / 50 = 38%, Nominated for studnet paper award!
24. Masanori HIRANO, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI, Taisei MUKAI,
    “Simulation of Unintentional Collusion Caused by Auto Pricing in Supply Chain Markets,”
    The 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2020), pp.352-359, Online, Nov. 19th, 2020.
    doi.org/10.1007/978-3-030-69322-0_24, detail
25. Masanori HIRANO, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Hiroki SAKAJI,
    “Comparison of Behaviors of Actual and Simulated HFT Traders for Agent Design,”
    The 22nd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2019), Torino, Italy, Oct. 31st, 2019.
    detail
    Accept rate (Long paper): 29 / 112 = 26%, Nominated for best paper award!: 3 / 112
    Published as a Journal article
26. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA,
    “mhirano at the FinSBD Task: Pointwise Prediction Based on Multi-layer Perceptron for Sentence Boundary Detection,”
    The First Workshop on Financial Technology and Natural Language Processing (FinNLP2019) in conjunction with the International Joint Conference on Artificial Intelligence (IJCAI) 2019, pp.102-107, Macao, China, Aug. 12th, 2019.
    aclanthology.org/W19-5518/, detail
27. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Selection of Related Stocks using Financial Text Mining,”
    The 1st International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC) in 2018 IEEE International Conference on Data Mining Workshops (ICDMW), pp.191-198, Singapore, Singapore, Nov. 17th, 2018.
    doi.org/10.1109/ICDMW.2018.00036, detail
28. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI, Takashi SHIMADA, Hiroyasu MATSUSHIMA,
    “Impact Assessments of the CAR Regulation using Artificial Markets,”
    International Workshop on Artificial Market 2018 (IWAM2018) in conjunction with The 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA2018), pp.43-58, Tokyo, Japan, Oct. 30th, 2018.
    www.u-mart.org/IWAM2018/CameraReady/IWAM2018_paper_2.pdf, detail

1. Masanori HIRANO, Kentaro IMAJO, Shuta SAITO, Shintarou OKADA, Kazuki MATOYA, Toru TANIGUCHI, Yoshiaki OTA,
   “Construction and Validation of a Financial LLMs,” [in Japanese]
   The 33rd meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.142-149, Kayaba-Cho, Tokyo, Japan, Oct. 20th, 2024.
   doi.org/10.11517/jsaisigtwo.2024.FIN-033_142, detail
2. Rushikesh HANDAL, Kazuki MATOYA, Yunzhuo WANG, Masanori HIRANO,
   “KAN-based Option Pricing Model for American and Asian Options,” [in Japanese]
   The 33rd meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.84-91, Kayaba-Cho, Tokyo, Japan, Oct. 19th, 2024.
   doi.org/10.11517/jsaisigtwo.2024.FIN-033_84, detail
3. Kei Nakagawa, Masanori Hirano, Yugo Fujimoto,
   “Evaluating company-specific bias in financial sentiment analysis using large language models,” [in Japanese]
   The 21st Text Analytics Symposium, vol.124, no.173, NLC2024-15, pp.81-86, Sapporo, Hokkaido, Japan, Sep. 3rd, 2024.
   ken.ieice.org/ken/paper/20240903bc4F/, detail
4. Kazuki Matoya, Yunzhuo Wang, Masanori Hirano, Kentaro Imajo,
   “Efficient Deep Hedging mechanism based on value function learning,” [in Japanese]
   The 38th Annual Conference of the Japanese Society for Artificial Intelligence, p.JSAI2024_4M3GS1002, Hamamatsu, Shizuoka, Japan, May 31st, 2024.
   doi.org/10.11517/pjsai.JSAI2024.0_4M3GS1002, detail
5. Kentaro Imajo, Kei Nakagawa, Kazuki Matoya, Masanori Hirano, Masana Aoki, Taku Imahase,
   “Residual return extraction using Principal Component Equivalence method,” [in Japanese]
   The 38th Annual Conference of the Japanese Society for Artificial Intelligence, p.JSAI2024_3D5GS205, Hamamatsu, Shizuoka, Japan, May 30th, 2024.
   doi.org/10.11517/pjsai.JSAI2024.0_3D5GS205, detail
6. Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta,
   “Impact of the number of AI traders on the market --Micro-foundations of the GARCH model,” [in Japanese]
   The 38th Annual Conference of the Japanese Society for Artificial Intelligence, p.JSAI2024_3Xin201, Hamamatsu, Shizuoka, Japan, May 30th, 2024.
   doi.org/10.11517/pjsai.JSAI2024.0_3Xin201, detail
7. Masanori Hirano,
   “Experiments of Deep Hedging using Artificial Market Simulation,” [in Japanese]
   The 38th Annual Conference of the Japanese Society for Artificial Intelligence, Hamamatsu, Shizuoka, Japan, May 29th, 2024.
   doi.org/10.11517/pjsai.JSAI2024.0_2F1GS503, detail
8. Masanori HIRANO,
   “Construction of a Japanese Financial Benchmark for Large Language Model Evaluation in the Financial Domain,” [in Japanese]
   30th Annual Meeting of the Association for Natural Language Processing (NLP2024), pp.1570-1574, Kobe, Hyogo, Japan, Mar. 18th, 2024.
   www.anlp.jp/proceedings/annual_meeting/2024/pdf_dir/C6-4.pdf, detail
9. Masanori HIRANO,
   “Construction of a Japanese Financial Benchmark for Large Language Model Evaluation in the Financial Domain and the Performances of Models,” [in Japanese]
   The 32nd meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.28-35, Shibuya, Tokyo, Japan, Mar. 2nd, 2024.
   doi.org/110.11517/jsaisigtwo.2023.FIN-032_28, detail
10. Masanori HIRANO, Ryoosuke TAKATA, Kiyoshi IZUMI,
    “PAMS: Platform for Artificial Market Simulations --Python-based Platform for Artificial Market Simulations and Challenges on its Integration with Deep Learning--,” [in Japanese]
    Joint Agent Workshops and Symposium 2023 (JAWS2023), Noboribetsu, Hokkaido, Japan, Sep. 13th, 2023.
    detail
11. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
    “LoRA Tuning Conversational Japanese Large Language Models using Japanese Instruction Dataset,” [in Japanese]
    The 20th Text Analytics Symposium, Sakai, Osaka, Japan, Sep. 6th, 2023.
    ken.ieice.org/ken/paper/20230906NCwg/, detail
12. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
    “llm-japanese-dataset v0: Building a Japanese chat dataset for large-scale language models,” [in Japanese]
    Special Interest Group on Natural Language Processing, Information Processing Society of Japan (SIG-NL, IPSJ), Yotsuya, Tokyo, Japan, Sep. 1st, 2023.
    id.nii.ac.jp/1001/00227482/, detail
13. Long CHENG, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Carbon Neutrality Scenarios of Industrial Consumers Combining Power Generation, Storage, and DR Using an Electricity Market Model,”
    The 37th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2023), Kumamoto, Japan, June 8th, 2023.
    doi.org/10.11517/pjsai.JSAI2023.0_3U1IS305, detail
14. Masanori HIRANO, Kiyoshi IZUMI,
    “Quantitative Evaluation of Multi-agent Simulation using Generative Adversarial Network -- An Alternative of Qualitative Evaluation for Artificial Market Simulation,”
    The 37th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2023), p.3U1IS301, Kumamoto, Japan, June 8th, 2023.
    doi.org/10.11517/pjsai.JSAI2023.0_3U1IS301, detail
15. Long CHENG, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Power Procurement Strategies of Industrial Consumers Combining Power Generation, Storage, and DR Using Electric Power Market Simulations,” [in Japanese]
    The 30th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.24-31, Bunkyo, Tokyo, Japan, Mar. 4th, 2023.
    doi.org/10.11517/jsaisigtwo.2023.FIN-030_24, detail
16. Masanori HIRANO, Kentaro MINAMI, Kentaro IMAJO,
    “Adversarial Deep Hedging Free from the Assumption of Underliers' Price Process,” [in Japanese]
    The 30th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.51-57, Bunkyo, Tokyo, Japan, Mar. 4th, 2023.
    doi.org/10.11517/jsaisigtwo.2023.FIN-030_51, detail
17. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,
    “Data-driven Agent Design for Artificial Market Simulation,”
    The 36th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2022), p.2S4IS2b01, Kyoto, Japan, June 15th, 2022.
    doi.org/10.11517/pjsai.JSAI2022.0_2S4IS2b01, detail
18. Masanori HIRANO, Kentaro IMAJO, Kentaro Minami, Takuya SHIMADA,
    “Nested Deep Hedging Mechanism for Multiple Options Hedging,” [in Japanese]
    The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.27-34, Bunkyo, Tokyo, Japan, Mar. 12th, 2022.
    doi.org/10.11517/jsaisigtwo.2022.FIN-028_27, detail
19. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Construction and Validation of a Pre-Training and Additional Pre-Training Financial Language Model,” [in Japanese]
    The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.132-137, Bunkyo, Tokyo, Japan, Mar. 12th, 2022.
    doi.org/10.11517/jsaisigtwo.2022.FIN-028_132, detail
20. Ryo WAKASUGI, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Demand Response Scenarios by Large Consumers Using an Electricity Market Model,” [in Japanese]
    The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.19-24, Bunkyo, Tokyo, Japan, Mar. 12th, 2022.
    doi.org/10.11517/jsaisigtwo.2022.FIN-028_19, detail
21. Ryo WAKASUGI, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Electricity Procurement Scenarios for Achieving Carbon Neutrality by Large Consumers,” [in Japanese]
    The 21st Special Interest Group on Data Oriented Constructive Mining and Simulation (DOCMAS), Rusutsu, Hokkai-do, Japan, Mar. 9th, 2022.
    collabodesign.org/docmas/2022/03/09/160/, detail
    Award wining!
22. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Construction and Validation of a Pre-Training Language Model Using Financial Documents,” [in Japanese]
    The 27th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.5-10, Online, Oct. 9th, 2021.
    sigfin.org/?027-02, detail
23. Rei TAGUCHI, Hikaru WATANABE, Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI, Kiyoshi IZUMI, Kenji HIRAMATSU,
    “Market Causality Analysis Using Polar Indicators Generated from Financial Texts,” [in Japanese]
    The 27th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.36-43, Online, Oct. 9th, 2021.
    sigfin.org/?027-07, detail
24. Masahiro SUZUMI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Performance Validation of Pre-Trained BERT in the Financial Domain,” [in Japanese]
    The 18th Text Analytics Symposium, IEICE Tech. Rep., vol.12, no.178, NLC2021-12, pp.26-29, Online, Sep. 16th, 2021.
    www.ieice.org/ken/paper/20210916yCfG/, detail
25. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,
    “STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets based on Residual Blocks or Transformers,”
    The 35th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2021), p.2N1-IS-2a-03, Online, June 9th, 2021.
    doi.org/10.11517/pjsai.JSAI2021.0_2N1IS2a03, detail
    Award wining!
26. Ryo Wakasugi, Kiyoshi Izumi, Masanori HIRANO,
    “Demand Responce Effectiveness Analysis Using Power Market Multi-Agent Simulation and Plant Power Consumption Model,” [in Japanese]
    The 35th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2021), p.2I3-GS-5b-04, Online, June 9th, 2021.
    doi.org/10.11517/pjsai.JSAI2021.0_2I3GS5b04, detail
27. Masanori HIRANO, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI, Hiroki SAKAJI,
    “STBM: Stochastic Trading Behavior Model for Financial Markets Based on Long Short-Term Memory,”
    The 34th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2020), p.1K4-ES-2-04, Online, June 9th, 2020.
    doi.org/10.11517/pjsai.JSAI2020.0_1K4ES204, detail
28. Masanori HIRANO, Hiroki SAKAJI, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI,
    “Unsupervised Extraction for Important Sentences in Financial Documents through Learning Other Tasks,” [in Japanese]
    26th Annual Meeting of the Association for Natural Language Processing (NLP2020), pp.569-572, Online, Mar. 18th, 2020.
    www.anlp.jp/proceedings/annual_meeting/2020/pdf_dir/B3-4.pdf, detail
29. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Development of Search Tool for Listed Company Related to ThemesUsing Text Mining,” [in Japanese]
    The 24th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.1-8, Kichijoji, Tokyo, Japan, Mar. 15th, 2020.
    sigfin.org/?024-41, detail
30. Masanori HIRANO, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Hiroki SAKAJI, Takashi SHIMADA,
    “Analysis of Limit Orders by High-Frequency Traders in Tokyo Stock Exchange,” [in Japanese]
    The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, p.2O1-J-13-04, Niigata, Niigata, Japan, June 5th, 2019.
    doi.org/10.11517/pjsai.JSAI2019.0_2O1J1304, detail
31. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Estimation of Hypernym or Hyponym using Word Co-occurrence in Documents,” [in Japanese]
    25th Annual Meeting of the Association for Natural Language Processing (NLP2019), pp.597-600, Nagoya, Aichi, Japan, Mar. 14th, 2019.
    www.anlp.jp/proceedings/annual_meeting/2019/pdf_dir/P3-22.pdf, detail
32. Masanori HIRANO, Hiroto YONENOH, Kiyoshi IZUMI,
    “Effects Analysis of CAR Regulations on Financial Markets using Artificial Market Simulations,” [in Japanese]
    The 32nd Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2018), p.2P205, Kagoshima, Kagoshima, Japan, June 6th, 2018.
    doi.org/10.11517/pjsai.JSAI2018.0_2P205, detail
    [Abstract Correction (Japanese)] / Award winning!

1. Masahiro Hirano,
   “Construction of a Japanese Financial Benchmark for Large Language Models,”
   arXiv:2403.15062 (doi.org/10.48550/arXiv.2403.15062), ssrn.com/abstract=4769124 (doi.org/10.2139/ssrn.4769124)
   detail
2. Masanori HIRANO,
   “Construction of a Japanese Financial Benchmark for Large Language Model Evaluation in the Financial Domain,” [in Japanese]
   doi.org/10.51094/jxiv.564, detail
3. Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano,
   “Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study,”
   arXiv:2311.07231 (doi.org/10.48550/arXiv.2311.07231), ssrn.com/abstract=4630864 (doi.org/10.2139/ssrn.4630864)
   detail
4. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
   “From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models,”
   arXiv:2309.03412 (doi.org/10.48550/arXiv.2309.03412), ssrn.com/abstract=4564308 (doi.org/10.2139/ssrn.4564308)
   doi.org/10.48550/arXiv.2309.03412, detail
5. Masanori HIRANO, Ryosuke TAKATA, Kiyoshi IZUMI,
   “PAMS: Platform for Artificial Market Simulations -- Python-based Platform for Artificial Market Simulations and\Challenges on its Integration with Deep Learning --,” [in Japanese]
   doi.org/10.51094/jxiv.461, detail
6. Masanori HIRANO, Kentaro MINAMI, Kentaro IMAJO,
   “Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling,”
   arXiv:2307.13217 (doi.org/10.48550/arXiv.2307.13217), ssrn.com/abstract=4520273 (doi.org/10.2139/ssrn.4520273)
   detail
7. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
   “LoRA Tuning Conversational Japanese Large Language Models using Japanese Instruction Dataset,” [in Japanese]
   doi.org/10.51094/jxiv.422, detail
8. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
   “llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models,” [in Japanese]
   doi.org/10.51094/jxiv.383, detail
9. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
   “llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodology,”
   arXiv:2305.12720 (doi.org/10.48550/arXiv.2305.12720), ssrn.com/abstract=4454626 (doi.org/10.2139/ssrn.4454626)
   detail
10. Masanori HIRANO, Kentaro IMAJO, Kentaro MINAMI, Takuya SHIMADA,
    “Efficient Learning of Nested Deep Hedging using Multiple Options,”
    arXiv:2305.12264 (doi.org/10.48550/arXiv.2305.12264), ssrn.com/abstract=4454377 (doi.org/10.2139/ssrn.4454377)
    detail
11. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,
    “Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets,”
    arXiv:2204.13338 (doi.org/10.48550/arXiv.2204.13338), ssrn.com/abstract=4095304 (doi.org/10.2139/ssrn.4095304)
    detail

1. Kentaro Imajo, Masanori Hirano, Shuji Suzuki, Hiroaki Mikami,
   "Benchmark for LLM Pre-training in Japanese: Evaluating Response Performance on Common Sense Specific to Japanese" (in Japanese)
   19th Symposium of Young Researcher Association for NLP Studies (Yans), Umeda, Osaka, Japan, Sep 6, 2024.
2. Masahiro SUZUKI, Masanori HIRANO, and Hiroki SAKAJI
   "Construction of Japanese Instruction Dataset and its Application to Tuning of Large-scale Language Models" (in Japanese)
   18th Symposium of Young Researcher Association for NLP Studies (Yans), Tokyo, Japan, August 31st, 2023
3. Masanori HIRANO,
   "Development and Application of Deep Hedging" (in Japanese)
   MPT Forum, Tokyo, Japan, June 1st, 2023
   https://mptforum.org/kiroku/season=2023
4. Masanori HIRANO, Kiyoshi IZUMI
   "Toward Quantitative Evaluation of Artificial Market Simulation Using GAN" (in Japanese)
   Symposium on Multi Agent Systems for Harmonization 2022 Summer Symposium, Hamamatsu, Shizuoka, Japan, Sep. 16th, 2022
   
5. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, and Kiyoshi IZUMI
   "Towards a Pre-Learning BERT Model for the Financial Domain" (in Japanese)
   16th Symposium of Young Researcher Association for NLP Studies (Yans), Online, August 31st, 2021
   
6. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI, and Hiroyasu MATSUSHIMA
   "Introduction of listed company search system related to theme" (in Japanese)
   14th Symposium of Young Researcher Association for NLP Studies (Yans), Sapporo, Hokkaido, Japan, August 26th, 2019
   
7. Masanori HIRANO,
   "SCM League: UTokyo Izumi Lab." in ANAC Session
   Twelfth International Workshop on Agent-based Complex Automated Negotiations (ACAN2019) in conjunction with IJCAI 2019, Macau, China, Aug. 11th, 2019
   

1. Masanori HIRANO, Taisei MUKAI, Hiroyasu MATSUSHIMA, and Kiyoshi IZUMI
   "Insurance Fraud Factory Manager Agent at ANAC2019 Supply Chain Management League,"
   The Tenth International Automated Negotiating Agents Competition (ANAC2019) of IJCAI 2019, Macau, China, Aug. 15th, 2019.
   Wins in 2 tracks!: 1st place in Standard Track & 1st place in Collusion Track

1. Apr. 2021 - Mar. 2024: Research Fellow (DC1) Grant, Japan Society for the Promotion of Science (JSPS), 9,700,000 JPY (Approx. 88,000 USD)

Current

1. Apr. 2024 - : Organizin Committee of IEEE Computational Intelligence in Financial Engineering and Economics (CIFEr 2026)
2. Aug. 2024 - : Program Committee of ACM International Conference on AI in Finance (ICAIF)
3. Apr. 2024 - : Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN) 幹事
4. Jan. 2023 - : Organizer of Applied Informatics in Finance and Economics (AIFE)
5. Apr. 2024 - : Program Committee of 15th International Conference on Smart Computing and Artificial Intelligence (SCAI 2024) in IIAI AAI 2024
6. Jan. 2024 -: Program Committee of Joint Workshop of the 7th Financial Technology and Natural Language Processing (FinNLP), the 5th Knowledge Discovery from Unstructured Data in Financial Services (KDF), and The 4th Workshop on Economics and Natural Language Processing (ECONLP)

Past

1. Apr. 2021 - Mar. 2023: Steering committee member of Japan Young Researcher Association for NLP Studies (YANS)

1. 特許6596565: 抽出システムおよびプログラム

1. japanese-lm-fin-harness (2023 release)
2. izumi-lab/llm-japanese-dataset (2023 release)
3. PAMS (2022 release)
4. pfhedge (2021 release)
5. PlhamJ (2019/04 release)
6. Plham v0.3 (2019/03 release)

1. Masanori HIRANO,
   "AAMAS 2022 (The 21st International Conference on Autonomous Agents and Multiagent Systems)", Journal of the Japanese Society for Artificial Intelligence, Vol.37, No.5, pp. 679-680, 2022. doi.org/10.11517/jjsai.37.5_679
2. Masanori HIRANO,
   教育用計算機システム(ECCS)相談員の声, in "Digital Life", Information Technology Center, The University of Tokyo, pp.30-31, Vol.30 (2018.3), 2018. ISSN: 1345-3017