TY - GEN
T1 - FinNLP-FNP-LLMFinLegal-2025 Shared Task
T2 - Joint Workshop of the 9th Financial Technology and Natural Language Processing, FinNLP 2025, the 6th Financial Narrative Processing, FNP 2025, and the 1st Workshop on Large Language Models for Finance and Legal, LLMFinLegal 2025, co-located with the 31st International Conference on Computational Linguistics, COLING 2025
AU - Wang, Keyi
AU - Patel, Jaisal
AU - Shen, Charlie
AU - Kim, Daniel
AU - Zhu, Andy
AU - Lin, Alex
AU - Borella, Luca
AU - Osborne, Cailean
AU - White, Matt
AU - Yang, Steve
AU - Xiao, Kairong
AU - Yanglet, Xiao Yang Liu
N1 - Publisher Copyright:
© 2025 Association for Computational Linguistics.
PY - 2025
Y1 - 2025
N2 - Financial large language models (FinLLMs) have been applied to various tasks in business, finance, accounting, and auditing. Complex financial regulations and standards are critical to financial services, which LLMs must comply with. However, FinLLMs’ performance in understanding and interpreting financial regulations has rarely been studied. Therefore, we organize the Regulations Challenge1, a shared task at COLING FinNLP-FNP-LLMFinLegal-2025. It encourages the academic community to explore the strengths and limitations of popular LLMs. We create 9 novel tasks and corresponding question sets. In this paper, we provide an overview of these tasks and summarize participants’ approaches and results. We aim to raise awareness of FinLLMs’ professional capability in financial regulations.
AB - Financial large language models (FinLLMs) have been applied to various tasks in business, finance, accounting, and auditing. Complex financial regulations and standards are critical to financial services, which LLMs must comply with. However, FinLLMs’ performance in understanding and interpreting financial regulations has rarely been studied. Therefore, we organize the Regulations Challenge1, a shared task at COLING FinNLP-FNP-LLMFinLegal-2025. It encourages the academic community to explore the strengths and limitations of popular LLMs. We create 9 novel tasks and corresponding question sets. In this paper, we provide an overview of these tasks and summarize participants’ approaches and results. We aim to raise awareness of FinLLMs’ professional capability in financial regulations.
UR - http://www.scopus.com/inward/record.url?scp=85217799797&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85217799797&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85217799797
T3 - Proceedings - International Conference on Computational Linguistics, COLING
SP - 363
EP - 370
BT - Joint Workshop of the 9th Financial Technology and Natural Language Processing, FinNLP 2025, the 6th Financial Narrative Processing, FNP 2025, and the 1st Workshop on Large Language Models for Finance and Legal, LLMFinLegal 2025
A2 - Chen, Chung-Chi
A2 - Moreno-Sandoval, Antonio
A2 - Huang, Jimin
A2 - Xie, Qianqian
A2 - Ananiadou, Sophia
A2 - Chen, Hsin-Hsi
Y2 - 19 January 2025 through 20 January 2025
ER -