Events Calendar

PhD Thesis Proposal - Fei Wang

PhD Thesis Proposal - Fei Wang

Committee Members: Muhao Chen (Chair), Laurent Itti, Aram Galstyan, Robin Jia, Tianshu Sun

Title: Robust and Context Faithful Language Understanding with (Large) Language Models

Abstract: Large language models (LLMs) have achieved remarkable success in various language understanding tasks. However, their deployment in real world scenarios raises significant accountability concerns. In this talk, I will begin with the contextual faithfulness issue. LLMs often rely on biased parametric knowledge to make unfaithful predictions. I will present a causality driven approach aimed at mitigating entity bias to ensure context faithful NLU. Subsequently, I will introduce the robustness issue against unknown prediction shortcuts. I will demonstrate how to address the issue by proactively mitigating attention biases. Finally, I will outline potential future directions for advancing LLM accountability

Audiences: Everyone Is Invited

Contact: Melissa Ochoa

Event Link: https://usc.zoom.us/j/92603629078?pwd=cnAyaFNPY1A5QTJ4Ny92K2NJdUlydz09