Zobrazeno 1 - 10
of 24 464
pro vyhledávání: '"Offensive language"'
Musicians frequently use social media to express their opinions, but they often convey different messages in their music compared to their posts online. Some utilize these platforms to abuse their colleagues, while others use it to show support for p
Externí odkaz:
http://arxiv.org/abs/2411.06477
Autor:
He, Jianfei, Wang, Lilin, Wang, Jiaying, Liu, Zhenyu, Na, Hongbin, Wang, Zimu, Wang, Wei, Chen, Qi
Identifying offensive language is essential for maintaining safety and sustainability in the social media era. Though large language models (LLMs) have demonstrated encouraging potential in social media analytics, they lack thorough evaluation when i
Externí odkaz:
http://arxiv.org/abs/2410.15623
Autor:
Mylonas, Nikolaos, Stylianou, Nikolaos, Tsikrika, Theodora, Vrochidis, Stefanos, Kompatsiaris, Ioannis
Interpretability is a topic that has been in the spotlight for the past few years. Most existing interpretability techniques produce interpretations in the form of rules or feature importance. These interpretations, while informative, may be harder t
Externí odkaz:
http://arxiv.org/abs/2410.10290
Offensive language detection is a crucial task in today's digital landscape, where online platforms grapple with maintaining a respectful and inclusive environment. However, building robust offensive language detection models requires large amounts o
Externí odkaz:
http://arxiv.org/abs/2407.20076
The prevalence of offensive content on the internet, encompassing hate speech and cyberbullying, is a pervasive issue worldwide. Consequently, it has garnered significant attention from the machine learning (ML) and natural language processing (NLP)
Externí odkaz:
http://arxiv.org/abs/2407.18738
Autor:
Matei, Vlad-Cristian, Tăiatu, Iulian-Marius, Smădu, Răzvan-Alexandru, Cercel, Dumitru-Clementin
This paper highlights the significance of natural language processing (NLP) within artificial intelligence, underscoring its pivotal role in comprehending and modeling human language. Recent advancements in NLP, particularly in conversational bots, h
Externí odkaz:
http://arxiv.org/abs/2409.20498
Autor:
Jim O’Driscoll
Why do people take offence at things that are said? What is it exactly about an offending utterance which causes this negative reaction? How well motivated is the response to the offence?Offensive Language addresses these questions by applying an arr
Detecting hate speech and offensive language is essential for maintaining a safe and respectful digital environment. This study examines the limitations of state-of-the-art large language models (LLMs) in identifying offensive content within systemat
Externí odkaz:
http://arxiv.org/abs/2406.12223
The proliferation of online offensive language necessitates the development of effective detection mechanisms, especially in multilingual contexts. This study addresses the challenge by developing and introducing novel datasets for offensive language
Externí odkaz:
http://arxiv.org/abs/2406.02169
The spread of various forms of offensive speech online is an important concern in social media. While platforms have been investing heavily in ways of coping with this problem, the question of privacy remains largely unaddressed. Models trained to de
Externí odkaz:
http://arxiv.org/abs/2404.11470