Live demonstration: A 1024-pixel CMOS multi-modality sensing array for cell-based assays. - Jong Seok Park 001; Moez Karim Aziz; Taiyun Chi; Amy Su; Andrew Zhao; Hee Cheol Cho; Mark P. Styczynski; Hua Wang 006 (IEEE SENSORS, 2016)

Graph-based extraction of shape features for leaf classification. - Andrew Zhao; Denis Tsygankov; Peng Qiu (GlobalSIP, 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 (GSI, 2017)

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)

IPC evolution thru declarative interface generation. - Nik Sultana; Saket; Andrew Zhao; Shubhendra Pal Singhal; Michael Kaplan; Rajesh Krishnan; Boon Thau Loo (DAI-SNAC@CoNEXT, 2021)

DMotion: Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos. - Haoqi Yuan; Ruihai Wu; Andrew Zhao; Haipeng Zhang 006; Zihan Ding; Hao Dong 003 (IROS, 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 (SUI, 2021)

Virtual Equipment System: Toward Peripersonal Equipment Slots with Machine Learning. - Mark Miller; Powen Yao; Adityan Jothi; Andrew Zhao; Sloan Swieso; Michael Zyda (SUI, 2021)

Toward Using Machine Learning-Based Motion Gesture for 3D Text Input. - Sloan Swieso; Powen Yao; Mark Miller; Adityan Jothi; Andrew Zhao; Michael Zyda (SUI, 2021)

Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos. - Haoqi Yuan; Ruihai Wu; Andrew Zhao; Haipeng Zhang 006; Zihan Ding; Hao Dong 003 (CoRR, 2021)

Provable General Function Class Representation Learning in Multitask Bandits and MDP. - Rui Lu; Andrew Zhao; Simon S. Du; Gao Huang 001 (NeurIPS, 2022)

A Mixture Of Surprises for Unsupervised Reinforcement Learning. - Andrew Zhao; Matthieu Gaetan Lin; Yangguang Li 001; Yong-Jin Liu 001; Gao Huang 001 (NeurIPS, 2022)

Provable General Function Class Representation Learning in Multitask Bandits and MDPs. - Rui Lu; Andrew Zhao; Simon S. Du; Gao Huang 001 (CoRR, 2022)

Quantum relaxation for quadratic programs over orthogonal matrices. - Andrew Zhao; Nicholas C. Rubin (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 001 (CoRR, 2023)

Augmenting Unsupervised Reinforcement Learning with Self-Reference. - Andrew Zhao; Erle Zhu; Rui Lu; Matthieu Lin; Yong-Jin Liu 001; Gao Huang 001 (CoRR, 2023)

Learning, Optimizing, and Simulating Fermions with Quantum Computers. - Andrew Zhao (CoRR, 2023)

Synthesizing Formal Network Specifications From Input-Output Examples. - Haoxian Chen 001; Chenyuan Wu; Andrew Zhao; Mukund Raghothaman; Mayur Naik; Boon Thau Loo (IEEE/ACM Trans. Netw., 2023)

Exploring Temporal Feature Correlation for Efficient and Stable Video Semantic Segmentation. - Matthieu Lin; Jenny Sheng; Yubin Hu 001; Yangguang Li 001; Lu Qi; Andrew Zhao; Gao Huang 001; Yong-Jin Liu 001 (AAAI, 2024)

ExpeL: LLM Agents Are Experiential Learners. - Andrew Zhao; Daniel Huang 007; Quentin Xu; Matthieu Lin; Yong-Jin Liu 001; Gao Huang 001 (AAAI, 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 001 (ACL (Findings), 2024)

Exploring Text-to-Motion Generation with Human Preference. - Jenny Sheng; Matthieu Lin; Andrew Zhao; Kevin Pruvost; Yu-Hui Wen; Yangguang Li 001; Gao Huang 001; Yong-Jin Liu 001 (CVPR Workshops, 2024)

Automatic Waterfowl and Habitat Detection using Drone Imagery and Deep Learning. - Andrew Zhao; Andrea Fratila; Yang Zhang; Zhenduo Zhai; Zhiguang Liu; Yi Shang (ICCE, 2024)

DiveR-CT: Diversity-enhanced Red Teaming with Relaxing Constraints. - Andrew Zhao; Quentin Xu; Matthieu Lin; Shenzhi Wang; Yong-Jin Liu 001; Zilong Zheng; Gao Huang 001 (CoRR, 2024)

Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories. - Yiqiao Jin; Andrew Zhao; Yeon-Chang Lee; Meng Ye 002; Ajay Divakaran; Srijan Kumar (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 001; Yong-Jin Liu 001 (CoRR, 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)

Expanding the reach of quantum optimization with fermionic embeddings. - Andrew Zhao; Nicholas C. Rubin (Quantum, 2024)

DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints. - Andrew Zhao; Quentin Xu; Matthieu Lin; Shenzhi Wang; Yong-Jin Liu 001; Zilong Zheng; Gao Huang 001 (AAAI, 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 001 (NAACL (Long Papers), 2025)

Learning the Structure of Any Hamiltonian from Minimal Assumptions. - Andrew Zhao (STOC, 2025)

Self-Referencing Agents for Unsupervised Reinforcement Learning. - Andrew Zhao; Erle Zhu; Rui Lu; Matthieu Lin; Yong-Jin Liu 001; Gao Huang 001 (Neural Networks, 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 001; Gao Huang 001 (Neural Networks, 2025)

Towards Understanding the Benefit of Multitask Representation Learning in Decision Process. - Rui Lu; Yang Yue; Andrew Zhao; Simon S. Du; Gao Huang 001 (CoRR, 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 001 (CoRR, 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 001 (CoRR, 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, 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; et al. (CoRR, 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, 2025)