Paper ID: 2306.15261

A Survey on Out-of-Distribution Evaluation of Neural NLP Models

Xinzhe Li, Ming Liu, Shang Gao, Wray Buntine

Adversarial robustness, domain generalization and dataset biases are three active lines of research contributing to out-of-distribution (OOD) evaluation on neural NLP models. However, a comprehensive, integrated discussion of the three research lines is still lacking in the literature. In this survey, we 1) compare the three lines of research under a unifying definition; 2) summarize the data-generating processes and evaluation protocols for each line of research; and 3) emphasize the challenges and opportunities for future work.

Submitted: Jun 27, 2023