Takehiro Takayanagi

According to our database, Takehiro Takayanagi authored at least 18 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

LLM agents reveal how human bias shapes path-dependent market dynamics.

Ryuji Hashimoto, Takehiro Takayanagi, Masahiro Suzuki, Kiyoshi Izumi

J. Comput. Soc. Sci., May, 2026

From Heard to Lived Opinions: Simulating Opinion Dynamics with Grounded LLM Agents in Economic Environments.

Ryuji Hashimoto, Masahiro Kaneko, Ryosuke Takata, Takehiro Takayanagi, Kiyoshi Izumi

CoRR, March, 2026

2025

PREFINE: Personalized Story Generation via Simulated User Critics and User-Specific Rubric Generation.

Kentaro Ueda, Takehiro Takayanagi

CoRR, October, 2025

The Impact and Feasibility of Self-Confidence Shaping for AI-Assisted Decision-Making.

Takehiro Takayanagi, Ryuji Hashimoto, Chung-Chi Chen, Kiyoshi Izumi

CoRR, February, 2025

Are Generative AI Agents Effective Personalized Financial Advisors?

Takehiro Takayanagi, Kiyoshi Izumi, Javier Sanz-Cruzado, Richard McCreadie, Iadh Ounis

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Agent-Based Simulation of a Financial Market with Large Language Models.

Ryuji Hashimoto, Takehiro Takayanagi, Masahiro Suzuki, Kiyoshi Izumi

Proceedings of the PRIMA 2025: Principles and Practice of Multi-Agent Systems, 2025

Can GPT-4 Sway Experts' Investment Decisions?

Takehiro Takayanagi, Hiroya Takamura, Kiyoshi Izumi, Chung-Chi Chen

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

CoFinDiff: Controllable Financial Diffusion Model for Time Series Generation.

Yuki Tanaka, Ryuji Hashimoto, Takehiro Takayanagi, Zhe Piao, Yuri Murayama, Kiyoshi Izumi

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Norm-Salvaged Embedding: Improving Condition Alignment of Synthetic Time Series Generation in Finance.

Ryuji Hashimoto, Yuki Tanaka, Takehiro Takayanagi, Zhe Piao, Kiyoshi Izumi

Proceedings of the 6th ACM International Conference on AI in Finance, 2025

FinPersona: An LLM-Driven Conversational Agent for Personalized Financial Advising.

Takehiro Takayanagi, Masahiro Suzuki, Kiyoshi Izumi, Javier Sanz-Cruzado, Richard McCreadie, Iadh Ounis

Proceedings of the Advances in Information Retrieval, 2025

2024

Incorporating Domain-Specific Traits into Personality-Aware Recommendations for Financial Applications.

Takehiro Takayanagi, Kiyoshi Izumi

New Gener. Comput., November, 2024

Beyond Turing Test: Can GPT-4 Sway Experts' Decisions?

Takehiro Takayanagi, Hiroya Takamura, Kiyoshi Izumi, Chung-Chi Chen

CoRR, 2024

Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis.

Takehiro Takayanagi, Masahiro Suzuki, Ryotaro Kobayashi, Hiroki Sakaji, Kiyoshi Izumi

Proceedings of the IEEE International Conference on Big Data, 2024

2023

Context-Aware Stock Recommendations with Stocks' Characteristics and Investors' Traits.

Takehiro Takayanagi, Kiyoshi Izumi

IEICE Trans. Inf. Syst., October, 2023

Personalized Stock Recommendation with Investors' Attention and Contextual Information.

Takehiro Takayanagi, Kiyoshi Izumi, Atsuo Kato, Naoyuki Tsunedomi, Yukina Abe

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Personalized Dynamic Recommender System for Investors.

Takehiro Takayanagi, Chung-Chi Chen, Kiyoshi Izumi

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Harnessing Behavioral Traits to Enhance Financial Stock Recommender Systems: Tackling the User Cold Start Problem.

Takehiro Takayanagi, Kiyoshi Izumi

Proceedings of the IEEE International Conference on Big Data, 2023

2022

SETN: Stock Embedding Enhanced with Textual and Network Information.

Takehiro Takayanagi, Hiroki Sakaji, Kiyoshi Izumi

Proceedings of the IEEE International Conference on Big Data, 2022