Domain-aware Self-supervised Pre-training for Label-Efficient Meme Analysis. (arXiv:2209.14667v1 [cs.CL])

Existing self-supervised learning strategies are constrained to either a
limited set of objectives or generic downstream tasks that predominantly target
uni-modal applications. This has isolated progress for imperative multi-modal
applications that are diverse in terms of complexity and domain-affinity, such
as meme analysis. Here, we introduce two self-supervised pre-training methods,
namely Ext-PIE-Net and MM-SimCLR that (i) employ off-the-shelf multi-modal
hate-speech data during pre-training and (ii) perform self-supervised learning
by incorporating multiple specialized pretext tasks, effectively catering to
the required complex …

analysis arxiv meme pre-training training