The article presents a study from IBM Research AI on creating efficient models for detecting hate, abuse, and profanity (HAP) in Large Language Models (LLMs). The authors highlight the importance…
Continue readingThe study critically examines the use of toxicity detection algorithms in proactive content moderation systems. It explores the potential misuse of these systems to circumvent detection, validate and gamify hate,…
Continue readingThis paper investigates the potential of GPT-4V in analyzing social media content. The study involves five tasks: sentiment analysis, hate speech detection, fake news identification, demographic inference, and political ideology…
Continue readingThis research explores the potential of large language models (LLMs) in detecting hate speech on social media platforms. The study evaluates LLMs such as GPT-3.5 and text-davinci on datasets like…
Continue readingThe paper, titled ‘Cordyceps@LT-EDI: Patching Language-Specific Homophobia/Transphobia Classifiers with a Multilingual Understanding’, presents a novel approach to detecting homophobia and transphobia in different languages. The approach combines multilingual (M-L) and…
Continue readingLooks like you're using an ad blocker. Please support us by disabling these ad blocker.
