Interventional training for out-of-distribution natural language understanding

• Main Authors: YU, Sicheng, JIANG, Jing, ZHANG, Hao, NIU, Yulei, SUN, Qianru, BING, Lidong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Natural language understanding; Out-of-domain detection; Dialogue system; Text classification; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/7548; https://ink.library.smu.edu.sg/context/sis_research/article/8551/viewcontent/Debias_Sicheng.pdf
• Institution: Singapore Management University

Out-of-distribution (OOD) settings are used to measure a model’s performance when the distribution of the test data is different from that of the training data. NLU models are known to suffer in OOD settings (Utama et al., 2020b). We study this issue from the perspective of causality, which sees con...