Mbias: Mitigating bias in large language models while retaining context

S Raza, A Raval, V Chatrath - ar** Safe and Responsible Large Language Model: Can We Balance Bias Reduction and Language Understanding in Large Language Models?
S Raza, O Bamgbose, S Ghuge, F Tavakol… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) have advanced various Natural Language Processing
(NLP) tasks, such as text generation and translation, among others. However, these models …

Make Satire Boring Again: Reducing Stylistic Bias of Satirical Corpus by Utilizing Generative LLMs

AU Ozturk, RF Cekinel - arxiv preprint arxiv:2412.09247, 2024 - arxiv.org
Satire detection is essential for accurately extracting opinions from textual data and
combating misinformation online. However, the lack of diverse corpora for satire leads to the …

Designing and debiasing binary classifiers for irony and satire detection

AU Öztürk - 2024 - open.metu.edu.tr
In the age of social media, detecting ironic and satirical text automatically is a challenging
task that is important for fighting misinformation online. Even though there are compelling …