Financial Technology (FinTech) is one of the worldwide rapidly-rising topics in the past five years according to the statistics of FinTech from Google Trends. In this position paper, we focus on the researches applying natural language processing (NLP) technologies in the finance domain. Our goal is to indicate the position we are now and provide the blueprint for future researches. We go through the application scenarios from three aspects including Know Your Customer (KYC), Know Your Product (KYP), and Satisfy Your Customer (SYC). Both formal documents and informal textual data are analyzed to understand corporate customers and personal customers. Furthermore, we talk over how to dynamically update the features of products from the prospect and the risk points of view. Finally, we discuss satisfying the customers in both B2C and C2C business models. After summarizing the past and the recent challenges, we highlight several promising future research directions in the trend of FinTech and the open finance tendency.
A Survey of Adversarial Defences and Robustness in NLP
Robert Bosch Centre for Data Science and AI（罗伯特·博世数据科学与人工智能中心）；Indian Institute of Technology Madras（印度理工学院马德拉斯分校）；Bhupat and Jyoti Mehta School of Biosciences（布帕特与乔蒂·梅塔生物科学学院）
Recent Trends in Deep Learning Based Natural Language Processing
Beijing Institute of Technology（北京理工大学）；National University of Singapore（新加坡国立大学）；Temasek Laboratories（淡马锡实验室）；Nanyang Technological University（南洋理工大学）
Out-of-Distribution Generalization in Text Classification: Past, Present, and Future
Westlake Institute for Advanced Study（西湖高等研究院）；University of Adelaide（阿德莱德大学）；Westlake University（西湖大学）；Dublin City University（都柏林城市大学）；Microsoft Research Asia（微软亚洲研究院）
Singapore Management University（新加坡管理大学）；CodeX, Stanford University, USA（CodeX，斯坦福大学，美国）；Illinois Tech - Chicago Kent College of Law, USA（伊利诺伊理工学院—芝加哥肯特法学院，美国）；Bucerius Law School, Germany（伯克勒尔法学院，德国）；IIT-Bhubaneswar（IIT-巴纳拉斯瓦尔）
A Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Study
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks
Institute of Artificial Intelligence, Leibniz University Hannover（汉诺威莱布尼茨大学人工智能学院）；Alma Mater Studiorum – University of Bologna（博洛尼亚大学）；German Research Center for Artificial Intelligence (DFKI)（德国人工智能研究中心）；L3S Research Center, Leibniz University Hannover（汉诺威莱布尼茨大学L3S研究中心）
