Improving Generalization in Coreference Resolution via Adversarial Training

Sanjay Subramanian, Dan Roth · 2019

In order for coreference resolution systems to be useful in practice, they must be able to generalize to new text.In this work, we demonstrate that the performance of the state-of-the-art system decreases when the names of PER and GPE named entities in the CoNLL dataset are changed to names that do not occur in the training set.We use the technique of adversarial gradient-based training to retrain the state-of-the-art system and demonstrate that the retrained system achieves higher performance on the CoNLL dataset (both with and without the change of named entities) and the GAP dataset.Original: But Dirk Van Dongen , president of the National Association of Wholesaler -Distributors , said that last month 's rise " is n't as bad an omen " as the 0.9 % figure suggests ." If you examine the data carefully , the increase is concentrated in energy and motor vehicle prices , rather than being a broad -based advance in the prices of consumer and industrial goods , " he explained .

Read the paper · More papers on PaperTik