3 citations · 17 across the 19 of their papers we have counts for
19 papers
Not What, But How: A Framework for Auditing LLM Responses across Positioning, Generalization, Anthropomorphism, and Maxims
Siddhesh Milind Pawar, Sarah Masud, Haneul Yoo +2
Large language models (LLMs) are being increasingly used to answer subjective, information-seeking questions, where users are sensitive to how responses are communicated, not just…
Scenario-based Probing and Steering Cultural Values in Large Language Models--Extended Version
Trung Duc Anh Dang, Tung Kieu, Sarah Masud
Large Language Models (LLMs) are deployed across cultural contexts but often reflect homogenized values inherited from training data. Evaluations of cultural alignment typically re…
Cultural Value Alignment Via Latent Activation Steering in Large Language Models
Trung Duc Anh Dang, Sarah Masud
Large Language Models (LLMs) often exhibit homogenized cultural perspectives. While the World Values Survey (WVS) provides a gold standard for mapping human values, traditional dir…
Listening Between the Lines: Decoding Podcast Narratives with Language Modeling
Shreya Gupta, Ojasva Saxena, Arghodeep Nandi +3
Podcasts have become a central arena for shaping public opinion, making them a vital source for understanding contemporary discourse. Their typically unscripted, multi-themed, and…
Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages
Tarek Naous, Anagha Savit, Carlos Rafael Catalan +17
As Large Language Models (LLMs) develop stronger multilingual capabilities, their sensitivity to culturally diverse entities becomes increasingly important. Prior work by Naous et…
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…
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…
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…
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…
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…
Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detection
Sarah Masud, Mohammad Aflah Khan, Md. Shad Akhtar +1
As hate speech continues to proliferate on the web, it is becoming increasingly important to develop computational methods to mitigate it. Reactively, using black-box models to ide…
Focal Inferential Infusion Coupled with Tractable Density Discrimination for Implicit Hate Detection
Sarah Masud, Ashutosh Bajpai, Tanmoy Chakraborty
Although pretrained large language models (PLMs) have achieved state-of-the-art on many natural language processing (NLP) tasks, they lack an understanding of subtle expressions of…
Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment
Atharva Kulkarni, Sarah Masud, Vikram Goyal +1
Social media is awash with hateful content, much of which is often veiled with linguistic and topical diversity. The benchmark datasets used for hate speech detection do not accoun…
Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization
Sarah Masud, Manjot Bedi, Mohammad Aflah Khan +2
Curbing online hate speech has become the need of the hour; however, a blanket ban on such activities is infeasible for several geopolitical and cultural reasons. To reduce the sev…
Handling Bias in Toxic Speech Detection: A Survey
Tanmay Garg, Sarah Masud, Tharun Suresh +1
Detecting online toxicity has always been a challenge due to its inherent subjectivity. Factors such as the context, geography, socio-political climate, and background of the produ…
DiVA: A Scalable, Interactive and Customizable Visual Analytics Platform for Information Diffusion on Large Networks
Dhruv Sahnan, Vasu Goel, Sarah Masud +3
With an increasing outreach of digital platforms in our lives, researchers have taken a keen interest to study different facets of social interactions that seem to be evolving rapi…
Fake News Detection System using XLNet model with Topic Distributions: CONSTRAINT@AAAI2021 Shared Task
Akansha Gautam, Venktesh V, Sarah Masud
With the ease of access to information, and its rapid dissemination over the internet (both velocity and volume), it has become challenging to filter out truthful information from…
Hate is the New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twitter
Sarah Masud, Subhabrata Dutta, Sakshi Makkar +4
Online hate speech, particularly over microblogging platforms like Twitter, has emerged as arguably the most severe issue of the past decade. Several countries have reported a stee…
Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity Prediction
Subhabrata Dutta, Sarah Masud, Soumen Chakrabarti +1
Modeling user engagement dynamics on social media has compelling applications in user-persona detection and political discourse mining. Most existing approaches depend heavily on k…