A Two-Stage Framework with Self-Supervised Distillation For Cross-Domain Text Classification

arXiv:2304.09820v2 Announce Type: replace
Abstract: Cross-domain text classification aims to adapt models to a target domain that lacks labeled data. It leverages or reuses rich labeled data from the different but related source domain(s) and unlabeled data from the target domain. To this end, previous work focuses on either extracting domain-invariant features or task-agnostic features, ignoring domain-aware features that may be present in the target domain and could be useful for the downstream task. In this paper, we propose a …

abstract adapt arxiv classification cs.ai cs.cl data distillation domain framework stage text text classification type work