PhD Dissertation Defense - Fei Wang

Title: Developing Robust and Controllable (Multimodal) Large Language Models      
Date and Time: Thur, Oct 31, 2024 @ 3:00 PM - 05:00 PM    
Location:  RTH 211  
Zoom Link: https://usc.zoom.us/my/feiwangnlp
Committee members: Aram Galstyan (Chair), Muhao Chen, Laurent Itti, Dan O’Leary      
 
Abstract:  As (multimodal) large language models (LLMs) become integral to intelligent systems, they are increasingly used in scenarios ranging from everyday applications to high-stakes domains such as healthcare, finance, and law. Consequently, there is a growing urgency to enhance the robustness and controllability of these models and mitigate critical risks in their development and deployment. This dissertation talk will introduce methods to ensure responsible outcomes from (multimodal) LLMs through three key perspectives: (1) dynamic integration of up-to-date and domain-specific knowledge, (2) robust alignment with human intents, preferences, and values, and (3) precise control over model behavior to ensure compliance with task constraints, authorization protocols, and safety requirements.

Location: Ronald Tutor Hall of Engineering (RTH) - 211

Audiences: Everyone Is Invited

Contact: Ellecia Williams