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Fighting Fire with Fire: Adversarial Prompting to Generate a Misinformation Detection Dataset
The recent success in language generation capabilities of large language models (LLMs), such as GPT, Bard, Llama etc., can potentially lead to concerns about their possible misuse in inducing mass agitation and communal hatred via generating fake news and spreading misinformation.
Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages
This paper presents the HASOC subtrack for English, Hindi, and Marathi.
Overview of the HASOC track at FIRE 2020: Hate Speech and Offensive Content Identification in Indo-European Languages
HASOC has two sub-task for all three languages: task A is a binary classification problem (Hate and Not Offensive) while task B is a fine-grained classification problem for three classes (HATE) Hate speech, OFFENSIVE and PROFANITY.
An Empirical Evaluation of Text Representation Schemes on Multilingual Social Web to Filter the Textual Aggression
Results show that text representation using BoW performs better than word embedding on machine learning classifiers.
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