The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing
November 20-23, 2022
Online and NTUH International Convention Center , Taiwan
Efficient and Robust Knowledge Graph Construction
Instructors: Ningyu Zhang, Tao Gui, Guoshun Nan
Knowledge graph construction which aims to extract knowledge from the text corpus has appealed to the NLP community researchers. Previous decades have witnessed the remarkable progress of knowledge graph construction on the basis of neural models; however, those models often cost massive computation or labeled data resources and suffer from unstable inference accounting for biased or adversarial samples. Recently, numerous approaches have been explored to mitigate the efficiency and robustness issues for knowledge graph construction, such as prompt learning and adversarial training. In this tutorial, we aim at bringing interested NLP researchers up to speed about the recent and ongoing techniques for efficient and robust knowledge graph construction. Additionally, our goal is to provide a systematic and up-to-date overview of these methods and reveal new research opportunities to the audience.
Grounding Meaning Representation for Situated Reasoning.
Instructors: Nikhil Krishnaswamy, James Pustejovsky
Recent Advances in Pre-trained Language Models: Why Do They Work and How Do They Work
Instructors: Cheng-Han Chiang, Yung-Sung Chuan, Hung-yi Lee
The Battlefront of Combating Misinformation and Coping with Media Bias
Instructors: Yi R. Fung, Kung-Hsiang Huang, Heng Ji, Preslav Nakov
The growth of online platforms has greatly facilitated the way people communicate with each other and stay informed about trending events. However, it has also spawned unprecedented levels of inaccurate or misleading information, as traditional journalism gate-keeping fails to keep up with the pace of media dissemination. These undesirable phenomena have caused societies to be torn over irrational beliefs, money lost from impulsive stock market moves, and deaths occurred that could have been avoided during the COVID-19 pandemic, due to the infodemic that came forth with it, etc. Even people who do not believe the misinformation may still be plagued by the pollution of unhealthy content surrounding them, an unpleasant situation known as information disorder. Thus, it is of pertinent interest for our community to better understand, and to develop effective mechanisms for remedying, misinformation and biased reporting.
When Cantonese NLP Meets Pre-training: Progress and Challenges
Instructors: Kam-Fai Wong, Mingyu Wan, Hanzhuo Tan, Rong Xiang, Jing Li
Cantonese is an influential Chinese variant with a large population of speakers worldwide. However, it is under-resourced in terms of the data scale and diversity, excluding Cantonese Natural Language Processing (NLP) from the state-of-the-art (SOTA) ``pre-training and fine-tuning'' paradigm. This tutorial will start with a substantially review of the linguistics and NLP progress for shaping language specificity, resources, and methodologies. It will be followed by an introduction to the trendy transformer-based pre-training methods, which have been largely advancing the SOTA performance of a wide range of downstream NLP tasks in numerous majority languages (e.g., English and Chinese). Based on the above, we will present the main challenges for Cantonese NLP in relation to Cantonese language idiosyncrasies of colloquialism and multilingualism, followed by the future directions to line NLP for Cantonese and other low-resource languages up to the cutting-edge pre-training practice.
A Tour of Explicit Multilingual Semantics: Word Sense Disambiguation, Semantic Role Labeling and Semantic Parsing
Instructors: Roberto Navigli, Rexhina Blloshmi, Edoardo Barba, Simone Conia