PhD Thesis Proposal - Ali Omrani

PhD Thesis Proposal - Ali Omrani
 
Committee Members: : Morteza Dehghani (Chair), Jeffrey Sorensen, Xiang Ren, Robin Jia, Jieyu Zhao, Payam Piray
 
Title: Countering Problematic Content in Digital Space: Bias Reduction and Dynamic Content Adaptation 
 
Abstract:  Problematic content, such as hate speech, poses a significant challenge to society, leading to discrimination and exclusion while undermining inclusivity and well-being. This thesis proposal outlines my efforts to create adaptable solutions for combating problematic content in digital space through a theory-motivated approach that bridges language technology and social sciences. I will begin by presenting an innovative group-agnostic method for bias mitigation in language models, which is grounded in a deep understanding of stereotyping from social psychology. Subsequently, I will introduce a novel continual learning framework for problematic content detection that captures the ever-evolving nature of this issue. Afterward, I discuss my strategy to extend this framework to multilingual settings, with a specific emphasis on two key aspects: 1. Harnessing cross-lingual information and 2. Investigating and overcoming the challenges posed by disparities in data quality across various languages.

Location: Seeley G. Mudd Building (SGM) - 605

Audiences: Everyone Is Invited

Contact: Melissa Ochoa