6 papers
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…
BEADs: Bias Evaluation Across Domains
Shaina Raza, Mizanur Rahman, Michael R. Zhang
Recent advances in large language models (LLMs) have substantially improved natural language processing (NLP) applications. However, these models often inherit and amplify biases p…
A Comprehensive Review of Recommender Systems: Transitioning from Theory to Practice
Shaina Raza, Mizanur Rahman, Safiullah Kamawal +4
Recommender Systems (RS) play an integral role in enhancing user experiences by providing personalized item suggestions. This survey reviews the progress in RS inclusively from 201…
Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives
Emrul Hasan, Mizanur Rahman, Chen Ding +2
Recommender systems play a pivotal role in helping users navigate an overwhelming selection of products and services. On online platforms, users have the opportunity to share feedb…
Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?
Shaina Raza, Oluwanifemi Bamgbose, Shardul Ghuge +3
Large Language Models (LLMs) have advanced various Natural Language Processing (NLP) tasks, such as text generation and translation, among others. However, these models often gener…
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…