FinIR: The 2nd Workshop on Financial Information Retrieval in the Era of Generative AI
Recent advancements in Generative AI, such as Large Language Models (LLMs), have demonstrated remarkable success across various general tasks. Extensive studies have explored leveraging generative models in finance, but significant challenges persist. This half-day workshop explores potential approaches and research directions to address these challenges by equipping generative models with advanced Information Retrieval (IR) models. Specifically, this workshop seeks to provide a platform for discussing innovative ideas that facilitate the advancement of IR technology to enrich generative models in finance from four key perspectives: (i) financial IR techniques (ii) financial IR benchmarking and evaluation (iii) financial systems and agents/assistants (iv) and trustworthiness, privacy and security when applying financial IR and generative models. This workshop aims to deepen understanding, accelerate progress, and support the advancement of IR technology to enhance generative models to address financial challenges.
Authors
- Guangnan Ye
- Fengbin Zhu (ORCID: https://orcid.org/0000-0001-6776-2040)
- Fuli Feng (ORCID: https://orcid.org/0000-0002-5828-9842)
- Dhagash Mehta (ORCID: https://orcid.org/0000-0002-1040-9032)
- Yunshan Ma (ORCID: https://orcid.org/0000-0003-3038-5389)
- Tat‐Seng Chua (ORCID: https://orcid.org/0000-0001-6097-7807)
- Huanbo Luan (ORCID: https://orcid.org/0000-0003-3938-119X)
- Pingping Chen
- Chao Wang (ORCID: https://orcid.org/0000-0002-7427-793X)
- Shuo Zhang (ORCID: https://orcid.org/0000-0003-3179-4125)
- Bing Xiang (ORCID: https://orcid.org/0009-0006-4028-4935)
Institutions
- University of Science and Technology of China (CN)
- National University of Singapore (SG)
- Fudan University (CN)
- Goldman Sachs (United States) (US)
- BlackRock (United States) (US)
- Singapore Management University (SG)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3730366
- Citations
- 1
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 2.11