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Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts
March 26, 2024, 4:51 a.m. | Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera
cs.CL updates on arXiv.org arxiv.org
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
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