University of Illinois at Urbana-Champaign
On the capabilities and risks of large language models
Abstract
dc:descriptionThe advent of Large Language Models (LLMs) has significantly influenced the field of artificial intelligence, offering remarkable text generation capabilities through their vast number of parameters. These advancements have established new benchmarks across various domains. However, despite the impressive capabilities of LLMs, there exist critical limitations and ethical challenges. This dissertation critically examines the capabilities of LLMs, including their reasoning abilities, and explores potential risks, such as privacy leakage. Through this analysis, we underscore the crucial need to improve the capabilities of LLMs while mitigating the associated risks. Based on this understanding, we propose methodologies to augment and safeguard LLMs. To enhance their functionality, we develop techniques to integrate LLMs with external knowledge and design an innovative data structure for knowledge representation. Additionally, we advocate for incorporating citation mechanisms within LLMs to promote transparency, accountability, and respect for intellectual property. Through rigorous research and the introduction of cutting-edge techniques, this dissertation aims to advance the capabilities of LLMs while ensuring their responsible and ethical use, ultimately contributing to the development of powerful and trustworthy artificial intelligence systems.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Huang, Jie
- Contributors dc:contributor
-
- Chang, Kevin Chen-Chuan
- Peng, Hao
- Tong, Hanghang
- Xu, Tianyin
- Yang, Diyi
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
-
- Copyright 2024 Jie Huang
- Language dc:language
- en, eng
Identifiers
dc:identifier.*- Handle dc:identifier
- https://hdl.handle.net/2142/125556