Zobrazeno 1 - 10
of 114
pro vyhledávání: '"Ng, Lynnette"'
Chatter on social media is 20% bots and 80% humans. Chatter by bots and humans is consistently different: bots tend to use linguistic cues that can be easily automated while humans use cues that require dialogue understanding. Bots use words that mat
Externí odkaz:
http://arxiv.org/abs/2501.00855
In recent years, mass-broadcast messaging platforms like Telegram have gained prominence for both, serving as a harbor for private communication and enabling large-scale disinformation campaigns. The encrypted and networked nature of these platforms
Externí odkaz:
http://arxiv.org/abs/2411.05922
Autor:
Ng, Lynnette Hui Xian, Chan, Luo Qi
Translation of code-mixed texts to formal English allow a wider audience to understand these code-mixed languages, and facilitate downstream analysis applications such as sentiment analysis. In this work, we look at translating Singlish, which is col
Externí odkaz:
http://arxiv.org/abs/2411.05253
Large Language Models (LLMs) offer a lucrative promise for scalable content moderation, including hate speech detection. However, they are also known to be brittle and biased against marginalised communities and dialects. This requires their applicat
Externí odkaz:
http://arxiv.org/abs/2410.20490
Autor:
Chan, Luo Qi, Ng, Lynnette Hui Xian
Singlish, or Colloquial Singapore English, is a language formed from oral and social communication within multicultural Singapore. In this work, we work on a fundamental Natural Language Processing (NLP) task: Parts-Of-Speech (POS) tagging of Singlis
Externí odkaz:
http://arxiv.org/abs/2410.16156
Singlish, or formally Colloquial Singapore English, is an English-based creole language originating from the SouthEast Asian country Singapore. The language contains influences from Sinitic languages such as Chinese dialects, Malay, Tamil and so fort
Externí odkaz:
http://arxiv.org/abs/2409.20366
Effective public health messaging benefits from understanding antecedents to unstable attitudes that are more likely to be influenced. This work investigates the relationship between moral and emotional bases for attitudes towards COVID-19 vaccines a
Externí odkaz:
http://arxiv.org/abs/2407.19406
Large Language Models (LLMs) have demonstrated remarkable capabilities in executing tasks based on natural language queries. However, these models, trained on curated datasets, inherently embody biases ranging from racial to national and gender biase
Externí odkaz:
http://arxiv.org/abs/2407.17688
Online multiplayer games like League of Legends, Counter Strike, and Skribbl.io create experiences through community interactions. Providing players with the ability to interact with each other through multiple modes also opens a Pandora box. Toxic b
Externí odkaz:
http://arxiv.org/abs/2407.04383
Autor:
Lim, Adrian Xuan Wei, Ng, Lynnette Hui Xian, Kyger, Nicholas, Michigami, Tomo, Baghernezhad, Faraz
Radiance fields produce high fidelity images with high rendering speed, but are difficult to manipulate. We effectively perform avatar texture transfer across different appearances by combining benefits from radiance fields and mesh surfaces. We repr
Externí odkaz:
http://arxiv.org/abs/2406.11570