What’s in a Domain? Learning Domain-Robust Text Representations using Adversarial Training
Table 1: Accuracy [%] of the different models over the seven heldout datasets, and the macro-averaged accuracy out-of-domain over the 7 test domains (“ALLout”). The best result for each dataset is indicated in bold. Key: +d = domain adversarial, +g = domain generation component.
['Models', 'EuroGov', 'TCL', 'Wikipedia2', 'EMEA', 'EuroPARL', 'T-BE', 'T-SC', 'ALLout']
Our primary concern in terms of evaluating the ability of the different models to generalise, is out-of-domain performance. The accuracy varies greatly between test domains, depending on the mix of languages, length of test documents, etc. Both our models, Cond and Gen, achieve competitive performance, and are further improved by d and g.