Pre-trained Large Language Models (LLMs) have shown tremendous potential in different areas and various tasks, including tasks in financial domain. The goal of this workshop is to bring together researchers and industry practitioners working on financial data mining and applying LLMs and machine learning technologies in financial services to share their ideas and best practices. It will feature paper presentations and invited talks or panel discussion on topics and research directions on big data for financial industry, especially using LLMs. Papers about original and ongoing research and those that describe systems and practices are welcome.

The Workshop will be co-located with 2024 IEEE International Conference on Big Data (IEEE BigData 2024). December 15-18, 2024. Washington DC, USA (Online or Hybrid)


The workshop welcomes submissions from a variety of topics, including but not limited to:

- Financial data preprocessing for use with LLMs
- Approaches and practices of human-in-the-loop for using LLMs in financial applications
- Fine-tuning LLMs for financial applications
- Using LLMs for market predication
- Using LLMs for different financial tasks, such as data collection, entity extraction, relation extraction, classification, clustering, novelty detection, event detection, summarization, translation, data integration, etc.
- LLMs application with different data types, e.g. social media, news, reports, and market data
- Domain adaptation and transfer learning using LLMs
- Knowledge graph (knowledge base, ontology) construction and completion with LLMs
- Question-answering and dialog system with LLMs
- Text to SQL using LLMs
- Decision making systems and trading algorithm using LLMs
- Analysis of financial reports and filings
- Use cases of multimodal LLMs for financial data
- Case studies and practices applying LLMs in financial services
- Privacy, fairness, ethical, legal, and other considerations of using LLMs in financial service
- Challenges of using LLMs in financial services
- Other research and applications of NLP or machine learning in financial services