ReZG: Retrieval-augmented zero-shot counter narrative generation for hate speech (Neurocomputing)
In order to produce CNs with a high level of specificity for invisible targets, the authors suggest Retrieval-Augmented Zero-shot Generation…
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Averting and Countering Online Hatred
In order to produce CNs with a high level of specificity for invisible targets, the authors suggest Retrieval-Augmented Zero-shot Generation…
The paper presents CoARL, a unique framework that models the pragmatic consequences of social biases in hostile remarks, hence improving…
It is currently common practice to train models for a range of NLP applications using synthetic data. Regarding its efficacy…
Because digital information is multimodal, regulating hate speech (HS) is a complex task in the ever changing world of online…
Researchers have created a new multi-task learning (MTL) model, a kind of machine learning model that functions across different datasets,…
The authors explore the idea of enhancing current data with generative language models, lowering target imbalance, given the unparalleled skills…
The study focuses on identifying hate speech in two languages in YouTube comments and evaluating how incorporating more data from…
There is still much to learn about how the hatred target’s traits interact with the annotator’s. To close this gap,…
The Office of Juvenile Justice and Delinquency Prevention (OJJDP) is preventing adolescent hate crimes and identity-based bullying in part with…
Unlike any other work that we are aware of, the study attempts to automatically detect hate speech using visual information…
There hasn’t been much research done on techniques for identifying HS in languages other than English, like Bengali. The survey…
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