SUTNLP at SemEval-2023 Task 4: LG-Transformer for Human Value Detection

When we interact with other humans, human values guide us to consider the human element. As we shall see, value analysis in NLP has been applied to personality profiling but not to argument mining. As part of SemEval-2023 Shared Task 4, our system paper describes a multi-label classifier for identifying human values. Human value detection requires multilabel classification since each argument may contain multiple values. In this paper, we propose an architecture called Label Graph Transformer (LG-Transformer). LG-Transformer is a two-stage pipeline consisting of a transformer jointly encoding argument and labels and a graph module encoding and obtaining further interactions between labels. Using adversarial training, we can boost performance even further. Our best method scored 50.00% using F1 score on the test set, which is 7.8% higher than the best baseline method. Our code is publicly available on Github.(1)