FinNLP-KDF-2024: Joint Workshop of the 7th Financial Technology and Natural Language Processing (FinNLP) and the 5th Knowledge Discovery from Unstructured Data in Financial Services (KDF)

LREC-COLING-2024
Torina, Italy, May 20, 2024

Conference website: https://sites.google.com/nlg.csie.ntu.edu.tw/finnlp-kdf-2024/home

Submission deadline: March 1, 2024

Introduction

FinNLP has emerged since 2019 as one of the pivotal workshops dedicated to harnessing NLP for financial technology applications. By collocating with representative conferences like IJCAI, EMNLP, and IJCNLP-AACL, it has bridged the AI and NLP communities. Its proceedings can be accessed on the ACL Anthology. On the other hand, KDF, initiated in 2020 as a workshop at AAAI, concentrates on multimodal knowledge discovery for financial services. It's particularly renowned for its keynote speaker series, inviting both academic and industry researchers to shed light on the latest topics. Recognizing the consistent efforts and contributions of both workshops over the years, we believe it's an opportune moment to convene their audiences, reflecting on achievements of the past five years and envisaging the roadmap for the next half-decade.

The adoption of artificial intelligence (AI) and machine learning (ML) in financial technology has been extensive. A significant observation is the diminishing barriers between diverse data modalities and also between distinct model architectures of different tasks. This progress emerges particularly after the inception of the Transformer model and potential of large language models (LLMs) as foundation models or generic resolvers of variety of NLP tasks. For instance, financial question-answering diverged from conventional machine reading comprehension tasks in NLP, such as SQuAD. This divergence was mainly attributed to the integration of knowledge from tabular data and image data. Given these advancements, we plan to expand the purview of both workshops. We are confident that such a merger will generate unprecedented synergy.

List of Topics

We invite submissions of original contributions on methods, theories, applications, and systems on artificial intelligence, machine learning, natural language processing & understanding, big data, statistical learning, data analytics, and deep learning, with a focus on knowledge discovery in the financial services domain. The scope of the workshop includes, but is not limited to, the following areas:

• Representation learning, and distributed representation learning and encoding in natural language processing for financial document
• Language modeling on financial corpora including tabular and numerical data, and multi-modal modeling; large language models (LLMs) and applications for finance
• Graph representation learning, mining learning on graph structures from financial data
• Multi-source knowledge integration and fusion, and knowledge alignment and integration from heterogeneous data
• Synthetic or genuine financial datasets and benchmarks for baseline models
• Transfer learning applications for financial data, knowledge distillation as a method for compression of pre-trained models or adaptation to financial datasets
• Search and question answering systems designed for financial corpora
• Event discovery from alternative data and impact on organization equity price
• Environmental, social, governance (ESG) event discovery, evaluation, and impact assessment

Submission Guidelines

Accepted papers proceedings will be published at ACL Anthology. 

Organizing Committees

Chung-Chi Chen, Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Japan

Xiaomo Liu, JP Morgan AI Research, US

Armineh Nourbakhsh, JP Morgan AI Research, US

Zhiqiang Ma, JP Morgan AI Research, US

Charese Smiley, JP Morgan AI Research, US

Manling Li, University of Illinois Urbana-Champaign, US 

Mohammad Ghassemi, Michigan State University, US

Hen-Hsen Huang, Institute of Information Science, Academia Sinica, Taiwan

Hiroya Takamura, Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Japan

Hsin-Hsi Chen, Department of Computer Science and Information Engineering, National Taiwan University, Taiwan

Venue

In conjunction with LREC-COLING-2024, May 20-25, 2024, Torina, Italia

Contact

For general inquiries about the workshop, please write to finnlp@nlg.csie.ntu.edu.tw.