FinLLM 2023: International Symposium on Large Language Models for Financial Services Sheraton Grand Macao Cotai Macao, China, August 20, 2023 |
Conference website | https://finllm.github.io/workshop/#/ |
Submission link | https://easychair.org/conferences/?conf=finllm2023 |
Submission deadline | June 20, 2023 |
Notification Due | July 4, 2023 |
Final Version Due | August 3, 2023 |
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. We encourage submissions that cover a wide range of topics including but not limited to techniques, applications, and challenges of large language models in financial services.
Submissions should be a maximum of 7 and a minimum of 4 pages including figures and tables in IJCAI’23 format. Additional pages containing only cited references are allowed. We do accept submissions of work recently published or currently under review. The submissions can contain author details. The workshop will not have formal proceedings, but authors of accepted abstracts can choose to have their work published on the workshop webpage. Selected papers from the workshop will be published in a special journal issue.
We recommend submitting your paper through EasyChair. The paper submission link is as follows:
https://easychair.org/conferences/?conf=finllm2023.
List of Topics (not limited to)
- Techniques
- Multimodal modeling of financial data using LLMs
- Preprocessing and cleaning of financial data for use with LLMs
- Integration of LLMs with other AI technologies in financial services
- Novel architectures and training techniques for LLMs in financial services.
- Scalability and efficiency of LLMs in financial services
- Cross-lingual and multilingual LLMs in financial services
- Human-in-the-loop approaches for LLMs in financial services
- Applications
- Financial forecasting using LLMs
- Sentiment analysis and opinion mining for financial data
- LLM-based trading algorithms and decision-making systems
- Analysis of financial news and social media using LLMs
- Semantic analysis of financial reports and filings
- Explainable AI in financial services using LLMs
- Transfer learning and domain adaptation for LLMs in financial services
- Case studies and success stories of LLMs in financial services
- Challenges
- Evaluation of LLMs for financial services
- Social economics and trustworthiness for LLMs in financial services
- Ethical and legal considerations in the use of LLMs in financial services
- Privacy and security concerns in the use of LLMs for financial data
- Bias and fairness considerations in the use of LLMs for financial services
Committees
Program Committee
- Adria Gascon (The Alan Turing Institute / University of Warwick)
- Anis Elgabli (University of Oulu)
- Aurélien Bellet (Inria)
- Ayfer Ozgur (Stanford University)
- Bai Shuo (Hengsheng Electronics Co Ltd.)
- Bingsheng He (National University of Singapore)
- Boi Faltings (Ecole Polytechnique Fédérale de Lausanne)
- Chaoping Xing (Nanyang Technological University)
- Chaoyang He (University of Southern California)
- Dimitrios Papadopoulos (Hong Kong University of Science and Technology)
- Fabio Casati (University of Trento)
- Farinaz Koushanfar (University of California San Diego)
- Fangkai Tang (E Fund)
- Gauri Joshi (Carnegie Mellon University)
- Graham Cormode (University of Warwick)
- Helen (Hai) Li (Duke University)
- Jalaj Upadhyay (Apple)
- Ji Feng (Sinnovation Ventures AI Institute)
- Jian Liu (Ping An Asset Management)
- Jianshu Weng (Swiss Re)
- Jihong Park (University of Oulu)
- Joshua Gardner (University of Michigan)
- Jun Zhao (Nanyang Technological University)
- Junyang Li (E Fund)
- Lalitha Sankar (Arizona State University)
- Leye Wang (Peking University)
- Marco Gruteser (Google)
- Martin Jaggi (Ecole Polytechnique Fédérale de Lausanne)
- Mehdi Bennis (University of Oulu)
- Mingshu Cong (The University of Hong Kong)
- Nguyen Tran (The University of Sydney)
- Ning Cheng (E Fund)
- Pingzhong Tang (Tsinghua University)
- Praneeth Vepakomma (MIT)
- Prateek Mittal (Princeton University)
- Rui Lin (Chalmers University of Technology)
- Sewoong Oh (University of Illinois at Urbana-Champaign)
- Shiqiang Wang (IBM)
- Siwei Feng (Nanyang Technological University)
- Tara Javidi (University of California San Diego)
- Xiaoyu Wang (E Fund)
- Yihan Jiang (University of Washington)
- Yongxin Tong (Beihang University)
- Tongzhe Zhang (E Fund)
- Yuxiang Wnag (E Fund)
- Zelei Liu (Nanyang Technological University)
- Zichen Chen (Nanyang Technological University)
- Yuanyuan Chen (Nanyang Technological University)
- Zheng Xu (University of Science and Technology of China)
- Zhengfei Li (E Fund)
Organizing Committee
- Shuoling Liu (E Fund)
- Xueyang Wu (Flaiverse)
- Yongpeng Tang (E Fund)
- Qian Xu (HKUST)
- Liyuan Chen (E Fund)
- Qiang Yang (WeBank/HKUST, Hong Kong)
Publication
FinLLM 2023 will not have formal proceedings, but authors of accepted abstracts can choose to have their work published on the workshop webpage. Selected papers from the workshop will be published in a special journal issue.
Contact
Symposium website: https://finllm.github.io/workshop/
All questions about submissions should be emailed to xwuba@connect.ust.hk or tangfangkai@efunds.com.cn