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Jiancheng Liu
( “*” indicates equal contribution.)
Jiancheng (JC) Liu
I am a Member of Technical Staff at OpenAI, working on LLM post-training. I am one of the
contributors to the GPT-5 series (GPT-5,
5.1, and 5.2) and the gpt-oss series.
I received my B.E. in computer science from the Institute for Interdisciplinary Information Sciences (Yao Class), Tsinghua University. I was fortunate to be advised by Prof. Shi-Min Hu on my undergraduate research and bachelor thesis. In 2018, I had some wonderful times working with Prof. Wojciech Matusik and Dr. Yuanming Hu at MIT.
Before joining OpenAI, I completed my M.S. degree in Computer Science at Michigan State University. During those two years, I focused on enhancing AI trustworthiness through Machine Unlearning in collaboration with Prof. Sijia Liu.
I am an AASI-certified level 1 snowboard instructor and was a baritone singer in the Tsinghua A Cappella Club. I love snowboarding and singing.
I received my B.E. in computer science from the Institute for Interdisciplinary Information Sciences (Yao Class), Tsinghua University. I was fortunate to be advised by Prof. Shi-Min Hu on my undergraduate research and bachelor thesis. In 2018, I had some wonderful times working with Prof. Wojciech Matusik and Dr. Yuanming Hu at MIT.
Before joining OpenAI, I completed my M.S. degree in Computer Science at Michigan State University. During those two years, I focused on enhancing AI trustworthiness through Machine Unlearning in collaboration with Prof. Sijia Liu.
I am an AASI-certified level 1 snowboard instructor and was a baritone singer in the Tsinghua A Cappella Club. I love snowboarding and singing.
Industrial Reports
Publications
Conferences
Towards Universal Mesh Movement Networks
NeurIPS 2024 (Spotlight)
Mingrui Zhang, Chunyang Wang, Stephan C. Kramer, Joseph G. Wallwork, Siyi Li, Jiancheng
Liu, Xiang Chen, Matthew D. Piggott
UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models
NeurIPS 2024 Datasets and Benchmarks
Yihua Zhang, Chongyu Fan, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu,
Gaoyuan Zhang, Gaowen Liu, Ramana Rao Kompella, Xiaoming Liu, Sijia Liu
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate
Unsafe Images... For Now
ECCV 2024
Yimeng Zhang*, Jinghan Jia*, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke
Ding, Sijia Liu
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image
Classification and Generation
ICLR 2024 (Spotlight)
Jiancheng Liu*, Chongyu Fan*, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training
ICLR 2024
Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu,
Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
Model Sparsity Can Simplify Machine Unlearning
NeurIPS 2023 (Spotlight)
Jiancheng Liu*, Jinghan Jia*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu,
Pranay Sharma, Sijia Liu
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning
NeurIPS 2023
Yihua Zhang*, Yimeng Zhang*, Aochuan Chen*, Jinghan Jia, Jiancheng Liu, Gaowen Liu,
Mingyi Hong, Shiyu Chang, Sijia Liu
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
ICRA 2019
Yuanming Hu, Jiancheng Liu*, Andrew Spielberg*, Joshua B. Tenenbaum, William T.
Freeman, Jiajun Wu, Daniela Rus, Wojciech Matusik
Delving Deep Into Coarse-to-Fine Framework for Facial Landmark Localization
CVPR 2017 Workshop
Xi Chen, Erjin Zhou, Yuchen Mo, Jiancheng Liu, Zhimin Cao
Journals
Deep Portrait Image Completion and Extrapolation
TIP 2020
Xian Wu, Rui-Long Li, Fang-Lue Zhang, Jian-Cheng Liu, Jue Wang, Ariel Shamir, Shi-Min
Hu