2 citations · 2 across the 5 of their papers we have counts for
6 papers
On Privacy in Data-Space Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics
Masoumeh Shafieinejad, D. B. Emerson, Behnoosh Zamanlooy +5
Tabular data plays an important role in many fields and industries, including those with elevated privacy considerations and risks. As such, there is a rising interest in generatin…
FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems
Val Andrei Fajardo, David B. Emerson, Amandeep Singh +5
Retrieval-augmented generation (RAG) systems have been shown to be effective in addressing many of the drawbacks of relying solely on the parametric memory of large language models…
Just as Humans Need Vaccines, So Do Models: Model Immunization to Combat Falsehoods
Shaina Raza, Rizwan Qureshi, Azib Farooq +4
Large language models (LLMs) reproduce misinformation not by memorizing false facts alone, but by learning the linguistic patterns that make falsehoods persuasive, such as hedging,…
FairSense-AI: Responsible AI Meets Sustainability
Shaina Raza, Mukund Sayeeganesh Chettiar, Matin Yousefabadi +2
In this paper, we introduce FairSense-AI: a multimodal framework designed to detect and mitigate bias in both text and images. By leveraging Large Language Models (LLMs) and Vision…
ViLBias: Detecting and Reasoning about Bias in Multimodal Content
Shaina Raza, Caesar Saleh, Azib Farooq +11
Detecting bias in multimodal news requires models that reason over text--image pairs, not just classify text. In response, we present ViLBias, a VQA-style benchmark and framework f…
Fact or Fiction? Can LLMs be Reliable Annotators for Political Truths?
Veronica Chatrath, Marcelo Lotif, Shaina Raza
Political misinformation poses significant challenges to democratic processes, shaping public opinion and trust in media. Manual fact-checking methods face issues of scalability an…