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Found 5 papers, 2 papers with code
Outlier Ranking in Large-Scale Public Health Streams
Disease control experts inspect public health data streams daily for outliers worth investigating, like those corresponding to data quality issues or disease outbreaks.
Harnessing Pre-Trained Sentence Transformers for Offensive Language Detection in Indian Languages
In our increasingly interconnected digital world, social media platforms have emerged as powerful channels for the dissemination of hate speech and offensive content.
Computationally Assisted Quality Control for Public Health Data Streams
However, existing outlier detection frameworks perform poorly on this task because they do not account for the data volume or for the statistical properties of public health streams.
L3Cube-IndicSBERT: A simple approach for learning cross-lingual sentence representations using multilingual BERT
We propose a simple yet effective approach to convert vanilla multilingual BERT models into multilingual sentence BERT models using synthetic corpus.
L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi
We evaluate these models on real text classification datasets to show embeddings obtained from synthetic data training are generalizable to real datasets as well and thus represent an effective training strategy for low-resource languages.
