Andrew Zhao

According to our database, Andrew Zhao authored at least 39 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation.

Yiran Wu, Mauricio Velazco, Andrew Zhao, Manuel Raúl Meléndez Luján, Srisuma Movva, Yogesh K. Roy, Quang Nguyen, Roberto Rodriguez, Qingyun Wu, Michael Albada, Julia Kiseleva, Anand Mudgerikar

CoRR, July, 2025

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning.

Shenzhi Wang, Le Yu, Chang Gao, Chujie Zheng, Shixuan Liu, Rui Lu, Kai Dang, Xionghui Chen, Jianxin Yang, Zhenru Zhang, Yuqiong Liu, An Yang, Andrew Zhao, Yang Yue, Shiji Song, Bowen Yu, Gao Huang, Junyang Lin

CoRR, June, 2025

MorphEUS: Morphable Omnidirectional Unmanned System.

Ivan Bao, José C. Díaz Peón González Pacheco, Atharva Navsalkar, Andrew Scheffer, Sashreek Shankar, Andrew Zhao, Hongyu Zhou, Vasileios Tzoumas

CoRR, May, 2025

Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

Andrew Zhao, Yiran Wu, Yang Yue, Tong Wu, Quentin Xu, Yang Yue, Matthieu Lin, Shenzhi Wang, Qingyun Wu, Zilong Zheng, Gao Huang

CoRR, May, 2025

Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Yang Yue, Zhiqi Chen, Rui Lu, Andrew Zhao, Zhaokai Wang, Yang Yue, Shiji Song, Gao Huang

CoRR, April, 2025

Towards Understanding the Benefit of Multitask Representation Learning in Decision Process.

Rui Lu, Yang Yue, Andrew Zhao, Simon S. Du, Gao Huang

CoRR, March, 2025

Corrigendum to "Self-Referencing agents for unsupervised reinforcement learning" [Neural Networks Volume 188, August 2025, 107448].

Andrew Zhao, Erle Zhu, Rui Lu, Matthieu Lin, Yong-Jin Liu, Gao Huang

Neural Networks, 2025

Self-Referencing Agents for Unsupervised Reinforcement Learning.

Andrew Zhao, Erle Zhu, Rui Lu, Matthieu Lin, Yong-Jin Liu, Gao Huang

Neural Networks, 2025

Learning the Structure of Any Hamiltonian from Minimal Assumptions.

Andrew Zhao

Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 2025

Model Surgery: Modulating LLM's Behavior Via Simple Parameter Editing.

Huanqian Wang, Yang Yue, Rui Lu, Jingxin Shi, Andrew Zhao, Shenzhi Wang, Shiji Song, Gao Huang

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints.

Andrew Zhao, Quentin Xu, Matthieu Lin, Shenzhi Wang, Yong-Jin Liu, Zilong Zheng, Gao Huang

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Expanding the reach of quantum optimization with fermionic embeddings.

Andrew Zhao, Nicholas C. Rubin

Quantum, 2024

Optimizing Social Media Annotation of HPV Vaccine Skepticism and Misinformation Using Large Language Models: An Experimental Evaluation of In-Context Learning and Fine-Tuning Stance Detection Across Multiple Models.

Luhang Sun, Varsha Pendyala, Yun-Shiuan Chuang, Shanglin Yang, Jonathan Feldman, Andrew Zhao, Munmun De Choudhury, Sijia Yang, Dhavan Shah

CoRR, 2024

LLM-based Optimization of Compound AI Systems: A Survey.

Matthieu Lin, Jenny Sheng, Andrew Zhao, Shenzhi Wang, Yang Yue, Yiran Wu, Huan Liu, Jun Liu, Gao Huang, Yong-Jin Liu

CoRR, 2024

Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories.

Yiqiao Jin, Andrew Zhao, Yeon-Chang Lee, Meng Ye, Ajay Divakaran, Srijan Kumar

CoRR, 2024

DiveR-CT: Diversity-enhanced Red Teaming with Relaxing Constraints.

Andrew Zhao, Quentin Xu, Matthieu Lin, Shenzhi Wang, Yong-Jin Liu, Zilong Zheng, Gao Huang

CoRR, 2024

Automatic Waterfowl and Habitat Detection using Drone Imagery and Deep Learning.

Andrew Zhao, Andrea Fratila, Yang Zhang, Zhenduo Zhai, Zhiguang Liu, Yi Shang

Proceedings of the IEEE International Conference on Consumer Electronics, 2024

Exploring Text-to-Motion Generation with Human Preference.

Jenny Sheng, Matthieu Lin, Andrew Zhao, Kevin Pruvost, Yu-Hui Wen, Yangguang Li, Gao Huang, Yong-Jin Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Boosting LLM Agents with Recursive Contemplation for Effective Deception Handling.

Shenzhi Wang, Chang Liu, Zilong Zheng, Siyuan Qi, Shuo Chen, Qisen Yang, Andrew Zhao, Chaofei Wang, Shiji Song, Gao Huang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

ExpeL: LLM Agents Are Experiential Learners.

Andrew Zhao, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, Gao Huang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Exploring Temporal Feature Correlation for Efficient and Stable Video Semantic Segmentation.

Matthieu Lin, Jenny Sheng, Yubin Hu, Yangguang Li, Lu Qi, Andrew Zhao, Gao Huang, Yong-Jin Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Synthesizing Formal Network Specifications From Input-Output Examples.

Haoxian Chen, Chenyuan Wu, Andrew Zhao, Mukund Raghothaman, Mayur Naik, Boon Thau Loo

IEEE/ACM Trans. Netw., June, 2023

Learning, Optimizing, and Simulating Fermions with Quantum Computers.

Andrew Zhao

CoRR, 2023

Augmenting Unsupervised Reinforcement Learning with Self-Reference.

Andrew Zhao, Erle Zhu, Rui Lu, Matthieu Lin, Yong-Jin Liu, Gao Huang

CoRR, 2023

Avalon's Game of Thoughts: Battle Against Deception through Recursive Contemplation.

Shenzhi Wang, Chang Liu, Zilong Zheng, Siyuan Qi, Shuo Chen, Qisen Yang, Andrew Zhao, Chaofei Wang, Shiji Song, Gao Huang

CoRR, 2023

Quantum relaxation for quadratic programs over orthogonal matrices.

Andrew Zhao, Nicholas C. Rubin

CoRR, 2023

2022

Provable General Function Class Representation Learning in Multitask Bandits and MDPs.

Rui Lu, Andrew Zhao, Simon S. Du, Gao Huang

CoRR, 2022

A Mixture Of Surprises for Unsupervised Reinforcement Learning.

Andrew Zhao, Matthieu Gaetan Lin, Yangguang Li, Yong-Jin Liu, Gao Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Provable General Function Class Representation Learning in Multitask Bandits and MDP.

Rui Lu, Andrew Zhao, Simon S. Du, Gao Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos.

Haoqi Yuan, Ruihai Wu, Andrew Zhao, Haipeng Zhang, Zihan Ding, Hao Dong

CoRR, 2021

Toward Using Machine Learning-Based Motion Gesture for 3D Text Input.

Sloan Swieso, Powen Yao, Mark Miller, Adityan Jothi, Andrew Zhao, Michael Zyda

Proceedings of the SUI '21: Symposium on Spatial User Interaction, 2021

Virtual Equipment System: Toward Peripersonal Equipment Slots with Machine Learning.

Mark Miller, Powen Yao, Adityan Jothi, Andrew Zhao, Sloan Swieso, Michael Zyda

Proceedings of the SUI '21: Symposium on Spatial User Interaction, 2021

Toward Predicting User Waist Location From VR Headset and Controllers Through Machine Learning.

Adityan Jothi, Powen Yao, Andrew Zhao, Mark Miller, Sloan Swieso, Michael Zyda

Proceedings of the SUI '21: Symposium on Spatial User Interaction, 2021

DMotion: Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos.

Haoqi Yuan, Ruihai Wu, Andrew Zhao, Haipeng Zhang, Zihan Ding, Hao Dong

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

IPC evolution thru declarative interface generation.

Nik Sultana, Saket, Andrew Zhao, Shubhendra Pal Singhal, Michael Kaplan, Rajesh Krishnan, Boon Thau Loo

Proceedings of the DAI-SNAC@CoNEXT 2021: Proceedings of the 2021 Workshop on Descriptive Approaches to IoT Security, 2021

2020

The No-Flippancy Game.

Isha Agarwal, Matvey Borodin, Aidan Duncan, Kaylee Ji, Tanya Khovanova, Shane Lee, Boyan Litchev, Anshul Rastogi, Garima Rastogi, Andrew Zhao

CoRR, 2020

2017

Prevalence and Recoverability of Syntactic Parameters in Sparse Distributed Memories.

Jeong-Joon Park, Ronnel Boettcher, Andrew Zhao, Alex Mun, Kevin Yuh, Vibhor Kumar, Matilde Marcolli

Proceedings of the Geometric Science of Information - Third International Conference, 2017

Graph-based extraction of shape features for leaf classification.

Andrew Zhao, Denis Tsygankov, Peng Qiu

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016

Live demonstration: A 1024-pixel CMOS multi-modality sensing array for cell-based assays.

Jong Seok Park, Moez Karim Aziz, Taiyun Chi, Amy Su, Andrew Zhao, Hee Cheol Cho, Mark P. Styczynski, Hua Wang

Proceedings of the 2016 IEEE SENSORS, Orlando, FL, USA, October 30 - November 3, 2016, 2016