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Andrew Zhao
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2020 – today
- 2024
- [c15]Matthieu Lin, Jenny Sheng, Yubin Hu, Yangguang Li, Lu Qi, Andrew Zhao, Gao Huang, Yong-Jin Liu:
Exploring Temporal Feature Correlation for Efficient and Stable Video Semantic Segmentation. AAAI 2024: 3450-3458 - [c14]Andrew Zhao, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, Gao Huang:
ExpeL: LLM Agents Are Experiential Learners. AAAI 2024: 19632-19642 - [c13]Shenzhi Wang, Chang Liu, Zilong Zheng, Siyuan Qi, Shuo Chen, Qisen Yang, Andrew Zhao, Chaofei Wang, Shiji Song, Gao Huang:
Boosting LLM Agents with Recursive Contemplation for Effective Deception Handling. ACL (Findings) 2024: 9909-9953 - [c12]Jenny Sheng, Matthieu Lin, Andrew Zhao, Kevin Pruvost, Yu-Hui Wen, Yangguang Li, Gao Huang, Yong-Jin Liu:
Exploring Text-to-Motion Generation with Human Preference. CVPR Workshops 2024: 1888-1899 - [c11]Andrew Zhao, Andrea Fratila, Yang Zhang, Zhenduo Zhai, Zhiguang Liu, Yi Shang:
Automatic Waterfowl and Habitat Detection using Drone Imagery and Deep Learning. ICCE 2024: 1-6 - [i16]Jenny Sheng, Matthieu Lin, Andrew Zhao, Kevin Pruvost, Yu-Hui Wen, Yangguang Li, Gao Huang, Yong-Jin Liu:
Exploring Text-to-Motion Generation with Human Preference. CoRR abs/2404.09445 (2024) - [i15]Andrew Zhao, Quentin Xu, Matthieu Lin, Shenzhi Wang, Yong-Jin Liu, Zilong Zheng, Gao Huang:
DiveR-CT: Diversity-enhanced Red Teaming with Relaxing Constraints. CoRR abs/2405.19026 (2024) - [i14]Yiqiao Jin, Andrew Zhao, Yeon-Chang Lee, Meng Ye, Ajay Divakaran, Srijan Kumar:
Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories. CoRR abs/2406.17963 (2024) - [i13]Huanqian Wang, Yang Yue, Rui Lu, Jingxin Shi, Andrew Zhao, Shenzhi Wang, Shiji Song, Gao Huang:
Model Surgery: Modulating LLM's Behavior Via Simple Parameter Editing. CoRR abs/2407.08770 (2024) - [i12]Matthieu Lin, Jenny Sheng, Andrew Zhao, Shenzhi Wang, Yang Yue, Yiran Wu, Huan Liu, Jun Liu, Gao Huang, Yong-Jin Liu:
LLM-based Optimization of Compound AI Systems: A Survey. CoRR abs/2410.16392 (2024) - [i11]Andrew Zhao:
Learning the structure of any Hamiltonian from minimal assumptions. CoRR abs/2410.21635 (2024) - 2023
- [j1]Haoxian Chen
, Chenyuan Wu, Andrew Zhao, Mukund Raghothaman
Synthesizing Formal Network Specifications From Input-Output Examples. IEEE/ACM Trans. Netw. 31(3): 994-1009 (2023) - [i10]Andrew Zhao, Nicholas C. Rubin:
Quantum relaxation for quadratic programs over orthogonal matrices. CoRR abs/2301.01778 (2023) - [i9]Andrew Zhao, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, Gao Huang:
ExpeL: LLM Agents Are Experiential Learners. CoRR abs/2308.10144 (2023) - [i8]Shenzhi Wang, Chang Liu, Zilong Zheng, Siyuan Qi, Shuo Chen, Qisen Yang, Andrew Zhao, Chaofei Wang, Shiji Song, Gao Huang:
Avalon's Game of Thoughts: Battle Against Deception through Recursive Contemplation. CoRR abs/2310.01320 (2023) - [i7]Andrew Zhao, Erle Zhu, Rui Lu, Matthieu Lin, Yong-Jin Liu, Gao Huang:
Augmenting Unsupervised Reinforcement Learning with Self-Reference. CoRR abs/2311.09692 (2023) - [i6]Andrew Zhao:
Learning, Optimizing, and Simulating Fermions with Quantum Computers. CoRR abs/2312.10399 (2023) - 2022
- [c10]Rui Lu, Andrew Zhao, Simon S. Du, Gao Huang:
Provable General Function Class Representation Learning in Multitask Bandits and MDP. NeurIPS 2022 - [c9]Andrew Zhao, Matthieu Gaetan Lin, Yangguang Li, Yong-Jin Liu, Gao Huang:
A Mixture Of Surprises for Unsupervised Reinforcement Learning. NeurIPS 2022 - [i5]Rui Lu, Andrew Zhao, Simon S. Du, Gao Huang:
Provable General Function Class Representation Learning in Multitask Bandits and MDPs. CoRR abs/2205.15701 (2022) - [i4]Andrew Zhao, Matthieu Gaetan Lin, Yangguang Li, Yong-Jin Liu, Gao Huang:
A Mixture of Surprises for Unsupervised Reinforcement Learning. CoRR abs/2210.06702 (2022) - 2021
- [c8]Nik Sultana, Saket, Andrew Zhao, Shubhendra Pal Singhal, Michael Kaplan, Rajesh Krishnan, Boon Thau Loo
IPC evolution thru declarative interface generation. DAI-SNAC@CoNEXT 2021: 17-21 - [c7]Haoqi Yuan, Ruihai Wu, Andrew Zhao, Haipeng Zhang, Zihan Ding, Hao Dong:
DMotion: Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos. IROS 2021: 7135-7142 - [c6]Adityan Jothi, Powen Yao, Andrew Zhao, Mark Miller, Sloan Swieso, Michael Zyda:
Toward Predicting User Waist Location From VR Headset and Controllers Through Machine Learning. SUI 2021: 27:1-27:2 - [c5]Sloan Swieso, Powen Yao, Mark Miller, Adityan Jothi, Andrew Zhao, Michael Zyda:
Toward Using Machine Learning-Based Motion Gesture for 3D Text Input. SUI 2021: 28:1-28:2 - [c4]Mark Miller, Powen Yao, Adityan Jothi, Andrew Zhao, Sloan Swieso, Michael Zyda:
Virtual Equipment System: Toward Peripersonal Equipment Slots with Machine Learning. SUI 2021: 30:1-30:2 - [i3]Haoqi Yuan, Ruihai Wu, Andrew Zhao, Haipeng Zhang, Zihan Ding, Hao Dong:
Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos. CoRR abs/2103.04301 (2021) - 2020
- [i2]Isha Agarwal, Matvey Borodin, Aidan Duncan, Kaylee Ji, Tanya Khovanova, Shane Lee, Boyan Litchev, Anshul Rastogi, Garima Rastogi, Andrew Zhao:
The No-Flippancy Game. CoRR abs/2006.09588 (2020)
2010 – 2019
- 2017
- [c3]Andrew Zhao, Denis Tsygankov
Graph-based extraction of shape features for leaf classification. GlobalSIP 2017: 663-666 - [c2]Jeong-Joon Park, Ronnel Boettcher, Andrew Zhao, Alex Mun, Kevin Yuh, Vibhor Kumar, Matilde Marcolli
Prevalence and Recoverability of Syntactic Parameters in Sparse Distributed Memories. GSI 2017: 265-272 - 2016
- [c1]Jong Seok Park, Moez Karim Aziz, Taiyun Chi, Amy Su, Andrew Zhao, Hee Cheol Cho, Mark P. Styczynski, Hua Wang
Live demonstration: A 1024-pixel CMOS multi-modality sensing array for cell-based assays. IEEE SENSORS 2016: 1 - 2015
- [i1]Jeong-Joon Park, Ronnel Boettcher, Andrew Zhao, Alex Mun, Kevin Yuh, Vibhor Kumar, Matilde Marcolli:
Prevalence and recoverability of syntactic parameters in sparse distributed memories. CoRR abs/1510.06342 (2015)
Coauthor Index
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