IJCAI-2023 Joint Workshop of the 5th Financial Technology and Natural Language Processing (FinNLP) and 2nd Multimodal AI For Financial Forecasting (Muffin)

19-25 August, 2023

Location: Macau

About the FinNLP workshop

The aim of this workshop is to provide a forum where international participants share knowledge on applying NLP to the FinTech domain. Recently, analyzing documents related to finance and economics has attracted much attention in the AI community. In the financial field, FinTech is a new industry that focuses on improving financial activity with technology. Thus, in order to bridge the gap between the NLP research and the financial applications, we organize FinNLP workshop series. One of the expected accomplishments of FinNLP is to introduce insights from the financial domain to the NLP community. With the sharing of the researchers in FinNLP, the challenging problems of blending FinTech and NLP will be identified, and the future research direction will be shaped. That can broaden the scope of this interdisciplinary research area.

About the Muffin workshop

The workshop aims to explore recent advances and challenges of multimodal AI for finance. Financial forecasting is an essential task that helps investors make sound investment decisions and wealth creation. With increasing public interest in trading stocks, cryptocurrencies, bonds, commodities, currencies, crypto coins and non-fungible tokens (NFTs), there have been several attempts to utilize unstructured data for financial forecasting. Unparalleled advances in multimodal deep learning have made it possible to utilize multimedia such as textual reports, news articles, streaming video content, audio conference calls, user social media posts, customer web searches, etc for identifying profit creation opportunities in the market. E.g., how can we leverage new and better information to predict movements in stocks and cryptocurrencies well before others? However, there are several hurdles towards realizing this goal - (1) large volumes of chaotic data, (2) combining text, audio, video, social media posts, and other modalities is non-trivial, (3) long context of media spanning multiple hours, days or even months, (4) user sentiment and media hype-driven stock/crypto price movement and volatility, (5) difficulties with traditional statistical methods (6) misinformation and non-interpretability of financial systems leading to massive losses and bankruptcies.

At the IJCAI-2023 Joint Workshop of the 5th Financial Technology and Natural Language Processing (FinNLP) and 2nd Multimodal AI For Financial Forecasting (MUFFIN), we aim to bring together researchers from multimodal AI community (natural language processing, computer vision, speech recognition, machine learning, statistics and quantitative trading) to expand research on the intersection of AI and finance.

We will also organize a shared tasks in this workshop – ESG Issue Identification.


This workshop will hold a research track and a shared task. The research track aims to explore recent advances and challenges of NLP & multimodal AI for finance. Researchers from artificial intelligence, computer vision, speech processing, natural language processing, data mining, statistics, optimization, and other fields are invited to submit papers on recent advances, resources, tools, and challenges on the broad theme of Multimodal AI for finance. The topics of the workshop include but are not limited to the following:

  • Transformer models / Self-supervised / Transfer Learning on Financial Data
  • Machine Learning for Finance
  • Natural Language Processing and Speech Applications for Finance
  • Conversational dialogue modeling for Financial Conference Calls
  • Social media and User NLP for Finance
  • Entity extraction and linking, Named-entity recognition, information extraction, relationship extraction, ontology learning in financial documents
  • Financial Document Processing
  • Multi-modal financial knowledge discovery
  • Financial Event detection from Multimedia
  • Visual-linguistic learning for financial video analysis
  • Video understanding (human behavior cognition, topic mining, facial expression detection, emotion detection, deception detection, gait and posture analysis, etc.)
  • Data annotation, acquisition, augmentation, feature engineering, for financial/time-series analysis
  • Bias analysis and mitigation in financial models and data
  • Statistical Modeling for Time Series Forecasting
  • Interpretability and explainability for financial AI models
  • Privacy-preserving AI for finance
Important Dates
  • March 30, 2023: IJCAI 2023 Workshop Website Open
  • April 26May 15, 2023: Submission Deadline Extended, visit CFP for more detail.
  • June 1, 2023: Paper notification
  • June 10, 2023: Camera-Ready Deadline
  • June 15, 2023: Early Registration Deadline
  • August 19-25, 2023: Workshop at IJCAI 2023

All deadlines are “anywhere on earth” (UTC-12)


Authors are invited to submit their unpublished work that represents novel research. The papers should be written in English using the IJCAI-23 author kit and follow the IJCAI 2023 formatting guidelines. Authors can also submit the supplementary materials, including technical appendices, source codes, datasets, and multimedia appendices. All submissions, including the main paper and its supplementary materials, should be fully anonymized. For more information on formatting and anonymity guidelines, please refer to IJCAI 2023 call for papers page. Reviewing: At least two reviewers with the matching technical expertise will review each paper.
Each paper should be accompanied by one workshop registration.
No Show Policy: At least one author of each accepted paper *must* travel to the IJCAI venue in person. Papers with “No Show” will be redacted. Multiple submissions of the same paper to more IJCAI workshops are forbidden.

All papers will be double blind peer reviewed. The workshop accepts both long papers and short papers:

  • Short Paper: Up to 4 pages of content, plus unlimited pages for references and appendix. Upon the acceptance, the authors are provided with 1 more page to address the reviewer's comments.

  • Long Paper: Up to 8 pages of content, plus unlimited pages for references and appendix. Upon the acceptance, the authors are provided with 1 more page to address the reviewer's comments.

  • Shared Task Track: Participants are invited to take part in the Multi-lingual ESG Issue Identification Task. Participants are invited to submit a system paper of 4-8 pages of content including the references.

Two reviewers with the same technical expertise will review each paper. Authors of the accepted papers will present their work in either the Oral or Poster session. All accepted papers will appear on the workshop proceedings that will be published in ACL Anthology. The authors will keep the copyright of their published papers.

Paper must be submitted using EasyChair. For information on System Paper submission for the share tasks, please refer to our shared tasks page.

Contact us: finnlp.muffin.ijcai2023@gmail.com