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Mavericks at BLP-2023 Task 1: Ensemble-based Approach Using Language Models for Violence Inciting Text Detection

arXiv 2311.18778 ↗First posted 30 Nov 2023cs.CLcited by 0

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Abstract (arXiv)

This paper presents our work for the Violence Inciting Text Detection shared task in the First Workshop on Bangla Language Processing. Social media has accelerated the propagation of hate and violence-inciting speech in society. It is essential to develop efficient mechanisms to detect and curb the propagation of such texts. The problem of detecting violence-inciting texts is further exacerbated in low-resource settings due to sparse research and less data. The data provided in the shared task consists of texts in the Bangla language, where each example is classified into one of the three categories defined based on the types of violence-inciting texts. We try and evaluate several BERT-based models, and then use an ensemble of the models as our final submission. Our submission is ranked 10th in the final leaderboard of the shared task with a macro F1 score of 0.737.

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References · 9

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  4. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
  5. 2021BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Banglacited by 125
  6. 2022L3Cube-HindBERT and DevBERT: Pre-Trained BERT Transformer models for Devanagari based Hindi and Marathi Languagescited by 35
  7. 2016Sentiment Analysis on Bangla and Romanized Bangla Text (BRBT) using Deep Recurrent modelscited by 7
  8. 2023BLP-2023 Task 2: Sentiment Analysiscited by 7
  9. 2023Interpretable Bangla Sarcasm Detection using BERT and Explainable AIcited by 2

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