This research group consists of interdisciplinary researchers who are interested in exploring various research topics related to large language models and vision language models.

Research Focus Area 

There are 4 subgroups focusing on different aspects of Large Language Models (LLMs) / Vision Language Models (VLMs) related research:
 
  1. Foundation models advancement (FMA)
    The FMA subgroup focuses on addressing the limitations of existing LLMs/VLMs, creating justifications for LLM results, and improving security & privacy of LLM/VLMs. 

    Sub group Leader: Jeff Heflin, Computer Science and Engineering, RCEAS
     
  2. Human-centric LLM (HCL)
    The HCL subgroup focuses on understanding how well LLMs/VLMs mimic human behaviors, how to address potential biases in LLM/VLM when they are being used to mimic human behaviors, how to mitigate against misinformation issues that are generated by LLMs/VLMs for example.
     
    Sub group Leader: Rebecca Wang, Marketing, College of Business
     
  3. LLM for CPS / Robotics (LCPS)
    The LCPS subgroup focuses on how to apply LLMs/VLMs to cyber physical systems and robots with formal guarantees. 

    Sub group Leader: Parv Venkitasubramaniam, Electrical and Computer Engineering, RCEAS
     
  4. LLM for healthcare (LLH)
    The LLH subgroup focuses on how to responsibly apply LLMs/VLMs to health care domains. This includes ensuring such models are fair, scalable and accurate.

    Sub group Leader: Mooi Choo Chuah, Computer Science and Engineering, RCEAS