I am a Ph.D. student in Computer Science at the University of Illinois Chicago. I am fortunate to be advised by Prof. Philip S. Yu. My general research area is machine learning, with an emphasis on Generative AI and Responsible AI.

Previously, I received my M.S. in Biomedical Data Science and Mathematics from University of Wisconsin-madison, where I am grateful to have worked with Prof. Yin Li and Prof. Vikas Singh. I received my B.S. in Mathematics from Sun Yat-sen University.

Preferred way of being contacted: lfang87 AT uic DOT edu

Publications

• TABGEN-RAG: Iterative Retrieval for Tabular Data Generation with Large Language Models

  Liancheng Fang, Aiwei Liu, Hengrui Zhang, Henry Peng Zou, Weizhi Zhang, Philip S. Yu

  3rd Table Representation Learning Workshop at NeurIPS 2024

• Diffusion-nested Auto-Regressive Synthesis of Heterogeneous Tabular Data

  *Hengrui Zhang, *Liancheng Fang, Qitian Wu, Philip S. Yu

  Preprint 2024

• Can Watermarked LLMs be Identified by Users via Crafted Prompts?

  Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang, Liancheng Fang, Lijie Wen, Philip S Yu, Xuming Hu

  Preprint 2024

• Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation

  Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Liancheng Fang, Philip S Yu

  CIKM 2024

• Unleashing the Potential of Diffusion Models for Incomplete Data Imputation

  Hengrui Zhang, Liancheng Fang, Philip S. Yu

  Preprint 2024

• ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction

  Henry Peng Zou, Vinay Samuel, Yue Zhou, Weizhi Zhang, Liancheng Fang, Zihe Song, Philip S. Yu, Cornelia Caragea

  ACL 2024 Findings