activity
20202026
most citedProactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization

3 citations · 17 across the 19 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.CL2024

Information Anxiety in Large Language Models

Prasoon Bajpai, Sarah Masud, Tanmoy Chakraborty

Large Language Models (LLMs) have demonstrated strong performance as knowledge repositories, enabling models to understand user queries and generate accurate and context-aware resp…

cs.CL2024★ 2 cited

Hate Personified: Investigating the role of LLMs in content moderation

Sarah Masud, Sahajpreet Singh, Viktor Hangya +2

For subjective tasks such as hate detection, where people perceive hate differently, the Large Language Model's (LLM) ability to represent diverse groups is unclear. By including a…

cs.SI2024★ 3 cited

Independent fact-checking organizations exhibit a departure from political neutrality

Sahajpreet Singh, Sarah Masud, Tanmoy Chakraborty

Independent fact-checking organizations have emerged as the crusaders to debunk fake news. However, they may not always remain neutral, as they can be selective in the false news t…

cs.CL2024★ 1 cited

Tox-BART: Leveraging Toxicity Attributes for Explanation Generation of Implicit Hate Speech

Neemesh Yadav, Sarah Masud, Vikram Goyal +2

Employing language models to generate explanations for an incoming implicit hate post is an active area of research. The explanation is intended to make explicit the underlying ste…

cs.CL2024

Probing Critical Learning Dynamics of PLMs for Hate Speech Detection

Sarah Masud, Mohammad Aflah Khan, Vikram Goyal +2

Despite the widespread adoption, there is a lack of research into how various critical aspects of pretrained language models (PLMs) affect their performance in hate speech detectio…