The 5th Workshop on Financial Technology and Natural Language Processing (FinNLP) and Multi-Lingual ESG Issue Identification (ML-ESG) Shared Task
In conjunction with IJCAI-2023, 20th August 2023, Macao
Room: Almaty 6002
Welcome to join the next FinNLP@IJCNLP-AACL-2023: https://sites.google.com/nlg.csie.ntu.edu.tw/finnlp2023/home
FinNLP-2023
This year, we are organizing a joint workshop with the 2nd Multimodal AI For Financial Forecasting (MUFFIN). We aim to bring together researchers from natural language processing, computer vision, speech recognition, machine learning, statistics and quantitative trading communities to expand research on the intersection of AI and finance. The joint workshop page: https://finnlp-muffin-ijcai23.github.io/
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.
Important Dates
April 26, 2023: Submission Deadline
May 11, 2023: Submission Deadline (Extended)
Submission System: https://easychair.org/conferences/?conf=finnlpmuffin2023
June 1, 2023: Paper notification
June 10, 2023: Camera-Ready Deadline
June 15, 2023: Early Registration Deadline
August 20, 2023: Workshop at IJCAI 2023
Time zone: Anywhere On Earth (AOE)
Accepted papers proceedings will be published at ACL Anthology.