Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts

arXiv:2403.16614v1 Announce Type: new
Abstract: Tasks such as semantic search and clustering on crisis-related social media texts enhance our comprehension of crisis discourse, aiding decision-making and targeted interventions. Pre-trained language models have advanced performance in crisis informatics, but their contextual embeddings lack semantic meaningfulness. Although the CrisisTransformers family includes a sentence encoder to address the semanticity issue, it remains monolingual, processing only English texts. Furthermore, employing separate models for different languages leads to embeddings in distinct vector spaces, introducing challenges …

arxiv crisis cross-lingual cs.cl embeddings media social social media type