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ORCIDLiqian Peng
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2020 – today
- 2026
[c7]Kai Zhang
, Congchao Wang, Liqian Peng, Alec Go, Xiaozhong Liu:
Privacy-preserved LLM Cascade via CoT-enhanced Policy Learning. WSDM 2026: 955-964- [i6]Wei-Lin Chen, Liqian Peng, Tian Tan, Chao Zhao, Blake JianHang Chen, Ziqian Lin, Alec Go, Yu Meng:
Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens. CoRR abs/2602.13517 (2026) - 2025
- [i5]Wenchong He, Liqian Peng, Zhe Jiang, Alex Go:
You Only Fine-tune Once: Many-Shot In-Context Fine-Tuning for Large Language Model. CoRR abs/2506.11103 (2025) - [i4]Devvrit Khatri, Pranamya Kulkarni, Nilesh Gupta, Yerram Varun, Liqian Peng, Jay Yagnik, Praneeth Netrapalli, Cho-Jui Hsieh, Alec Go, Inderjit S. Dhillon, Aditya Kusupati, Prateek Jain:
Compressing Many-Shots in In-Context Learning. CoRR abs/2510.16092 (2025) - 2024
- [i3]Kai Zhang, Liqian Peng, Congchao Wang, Alec Go, Xiaozhong Liu:
LLM Cascade with Multi-Objective Optimal Consideration. CoRR abs/2410.08014 (2024) - 2021
- [j5]Zhe Bai, Liqian Peng:
Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators. Adv. Model. Simul. Eng. Sci. 8(1): 28 (2021) - [i2]Zhe Bai, Liqian Peng:
Non-intrusive Nonlinear Model Reduction via Machine Learning Approximations to Low-dimensional Operators. CoRR abs/2106.09658 (2021)
2010 – 2019
- 2019
- [j4]Kevin T. Carlberg, Antony Jameson, Mykel J. Kochenderfer, Jeremy Morton, Liqian Peng, Freddie D. Witherden:
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning. J. Comput. Phys. 395: 105-124 (2019) - 2018
- [i1]Kevin T. Carlberg, Antony Jameson, Mykel J. Kochenderfer, Jeremy Morton, Liqian Peng, Freddie D. Witherden:
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning. CoRR abs/1812.01177 (2018) - 2016
- [j3]Liqian Peng, Kamran Mohseni:
Symplectic Model Reduction of Hamiltonian Systems. SIAM J. Sci. Comput. 38(1) (2016) - [c6]Liqian Peng, Kamran Mohseni:
Geometric model reduction of forced and dissipative Hamiltonian systems. CDC 2016: 7465-7470 - 2015
- [c5]Liqian Peng, Kamran Mohseni:
A localized symplectic model reduction technique for parameterized Hamiltonian systems. ACC 2015: 5545-5550 - [c4]Liqian Peng, Matthew Silic, Kamran Mohseni:
A DDDAS Plume Monitoring System with Reduced Kalman Filter1. ICCS 2015: 2533-2542 - 2014
- [j2]Liqian Peng, Doug Lipinski, Kamran Mohseni:
Dynamic Data Driven Application System for Plume Estimation Using UAVs. J. Intell. Robotic Syst. 74(1-2): 421-436 (2014) - [j1]Liqian Peng, Kamran Mohseni:
An Online Manifold Learning Approach for Model Reduction of Dynamical Systems. SIAM J. Numer. Anal. 52(4): 1928-1952 (2014) - [c3]Isaac J. Sledge, Liqian Peng, Kamran Mohseni:
An Empirical Reduced Modeling Approach for Mobile, Distributed Sensor Platform Networks. DyDESS 2014: 195-204 - 2013
- [c2]Bobby Hodgkinson, Doug Lipinski, Liqian Peng, Kamran Mohseni:
Cooperative control using data-driven feedback for mobile sensors. ICRA 2013: 772-777 - 2012
- [c1]Bobby Hodgkinson, Doug Lipinski, Liqian Peng, Kamran Mohseni:
High Resolution Atmospheric Sensing Using UAVs. DARS 2012: 31-45
Coauthor Index
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