Hi There

Hi there! I am a first-year PhD student in Computer Science, at University of California, Los Angeles, advised by Prof. Saadia Gabriel. Previously I received my Master’s degree in CS at Univeristy of Illinois Urbana-Champaign, and undergraduate degrees in both Computer Science and Mathematics from University of Massachusetts, Amherst. I’ve worked as a graduate research assistant with Prof. Heng Ji at the BLENDER Lab, and Prof. Hao Peng at UIUC as well. Before that, I worked at the Information Fusion Lab advised by Prof. Ina Fiterau and the TRIPODS Institute for Theoretical Foundations of Data Science at UMass Amherst advised by Prof. Yulong Lu as a research intern.

Research Interests

I’m broadly interested in studying and evaluating Large Language Models, and mitigating the undesirable behaviors such as hallucinated and harmful content. Recently I’ve also been working on many topics relevant to simulation agents, scalable oversight, and cognitive architectures of LLMs.

Education

• University of California, Los Angeles
  • Ph.D. in Computer Science, 2024-present, advised by Prof. Saadia Gabriel
• University of Illinois, Urbana-Champaign
  • Master in Computer Science, 2022-2023, advised by Prof. Heng Ji and Prof. Hao Peng
• University of Massachusetts, Amherst
  • B.S. in Computer Science, 2018-2022
  • B.S. in Mathematics, 2018-2022
  • Degree Honors: Commonwealth Honors Scholar with Greatest Distinction

Publications

For the most up to date list of publications, please refer to my Semantic Scholar profile.

• SciCode: A Research Coding Benchmark Curated by Scientists
  Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, Xinan Chen, Cunwei Fan, Xuefei Guo, Roland Haas, Pan Ji, Kittithat Krongchon, Yao Li, Shengyan Liu, Di Luo, Yutao Ma, Hao Tong, Kha Trinh, Chenyu Tian, Zihan Wang, Bohao Wu, Yanyu Xiong, Shengzhu Yin, Minhui Zhu, Kilian Lieret, Yanxin Lu, Genglin Liu, Yufeng Du, Tianhua Tao, Ofir Press, Jamie Callan, Eliu Huerta, Hao Peng
  NeurIPS 2024 Datasets and Benchmarks track [paper]
• Examining LLMs’ Uncertainty Expression Towards Questions Outside Parametric Knowledge
  Genglin Liu, Xingyao Wang, Lifan Yuan, Yangyi Chen, Hao Peng
  Preprint 2023 [paper]
• Paxion: Patching Action Knowledge in Video-Language Foundation Models
  Zhenhailong Wang, Ansel Blume, Sha Li, Genglin Liu, Jaemin Cho, Zineng Tang, Mohit Bansal, Heng Ji
  NeurIPS 2023, Spotlight [Paper]
• An Augmented Multilingual NLI Approach Towards Online News Persuasion Techniques Detection
  Genglin Liu, Yi R. Fung, Heng Ji
  Proceedings of the The 17th International Workshop on Semantic Evaluation [paper]
• Schematic Event Representation: An Empirical Approach to Hierarchical Schema Curation
  Reece Suchocki, Mary Lynn Martin, Genglin Liu, Martha Palmer, Susan Brown
  Preprint, 2023
• Forecasting Alzheimer’s Disease Two Years Ahead from Longitudinal Multimodal Data
  Sidong Zhang, Evan Fellman, James Ko, Genglin Liu, Madalina Fiterau
  Preprint, 2023
• Demystifying The Spectral Bias of Overparameterized Deep Neural Networks
  Genglin Liu, Yulong Lu
  UConn REU Conference, 2021 [technical report]
• Hybrid Convolution and Deep Learning with Structured Covariates
  Genglin Liu, Madalina Fiterau
  Undergraduate Honors Thesis, 2022 [thesis manuscript]

Internships/Research Experiences

Spring 2024 - Present: Department of Computer Science, UIUC

• Research Assistant
• Advisor: Hao Peng
• Projects: Uncertainty Expression in Large Language Models

Fall 2022 - Fall 2023: BLENDER NLP Lab, Urbana IL

• Graduate Research Assistant
• Advisor: Heng Ji
• Projects: Multimodal learning, multilingual-NLP

Summer 2022: BLENDER NLP Lab, Urbana IL

• Research Intern
• Advisor: Heng Ji
• Project: Multimedia misinformation detection

Summer 2021: TRIPODS Institute for Theoretical Foundations of Data Science, Amherst MA

• Research Intern
• Advisor: Yulong Lu
• Project: spectral properties and learnability of Neural Tangent Kernels with different activation functions

Fall 2020 - Spring 2022: InfoFusion Lab, Amherst MA

• Undergrad Research Assistant
• Advisor: Ina Fiterau
• Project: Hybrid convolutional neural networks which take visual and tabular data as multimodal input. (Undergraduate Honors Thesis)

Mentoring/Teaching Experiences

• Course Assistant
  CS 311: Algorithms, spring 2021
  CS 250: Discrete Mathematics, fall 2020
  College of Information and Computer Sciences, UMass Amherst
• Undergraduate Teaching Assistant
  Math 103: Calculus I, fall 2019
  Math 104: Calculus II, spring 2020
  Department of Mathematics and Statistics, UMass Amherst
• Residential Peer Mentor
  Fall 2019 - Fall 2022, UMass Amherst

Awards and Honors

• College of Information and Computer Sciences Departmental Honors, 2022
• Bay State Fellowship Recipient at UMass Amherst, 2022 (declined)
• Chancellor’s Award at UMass Amherst, 2018 ($56000)

Service

ACL reviewer, 2024