Detection of drift sensor faults in a class of nonlinear uncertain systems. - Yilun Zhou; Thomas Parisini; Marios M. Polycarpou (CDC, 2015)

Distributed fault detection with sensor networks using pareto-optimal dynamic estimation method. - Yilun Zhou; Francesca Boem; Carlo Fischione; Thomas Parisini (ECC, 2016)

Representing and Learning Complex Object Interactions. - Yilun Zhou; George Dimitri Konidaris (Robotics: Science and Systems, 2016)

Asymptotically Optimal Planning by Feasible Kinodynamic Planning in a State-Cost Space. - Kris Hauser; Yilun Zhou (IEEE Trans. Robotics, 2016)

Partition-based Pareto-optimal state prediction method for interconnected systems using sensor networks. - Yilun Zhou; Francesca Boem; Thomas Parisini (ACC, 2017)

Incorporating side-channel information into convolutional neural networks for robotic tasks. - Yilun Zhou; Kris Hauser (ICRA, 2017)

Representing, learning, and controlling complex object interactions. - Yilun Zhou; Benjamin Burchfiel; George Dimitri Konidaris (Auton. Robots, 2018)

Distributed Pareto-optimal state estimation using sensor networks. - Francesca Boem; Yilun Zhou; Carlo Fischione; Thomas Parisini (Autom., 2018)

Low-precision CNN Model Quantization based on Optimal Scaling Factor Estimation. - Yilun Zhou; Li Chen 021; Rong Xie; Li Song 001; Wenjun Zhang 001 (BMSB, 2019)

Learning Household Task Knowledge from WikiHow Descriptions. - Yilun Zhou; Julie Shah; Steven Schockaert (SemDeep@IJCAI, 2019)

Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness. - Yilun Zhou; Steven Schockaert; Julie Shah (WWW, 2019)

On Memory Mechanism in Multi-Agent Reinforcement Learning. - Yilun Zhou; Derrik E. Asher; Nicholas R. Waytowich; Julie A. Shah (CoRR, 2019)

Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach. - Serena Booth; Ankit Shah 003; Yilun Zhou; Julie Shah (CoRR, 2020)

Adversarially Guided Self-Play for Adopting Social Conventions. - Mycal Tucker; Yilun Zhou; Julie Shah (CoRR, 2020)

Bayes-Probe: Distribution-Guided Sampling for Prediction Level Sets. - Serena Booth; Yilun Zhou; Ankit J. Shah; Julie A. Shah (CoRR, 2020)

Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example. - Serena Booth; Yilun Zhou; Ankit Shah 003; Julie Shah (AAAI, 2021)

Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms. - Yilun Zhou; Adithya Renduchintala; Xian Li 003; Sida Wang 001; Yashar Mehdad; Asish Ghoshal (AISTATS, 2021)

RoCUS: Robot Controller Understanding via Sampling. - Yilun Zhou; Serena Booth; Nadia Figueroa; Julie Shah (CoRL, 2021)

Reducing spatial autocorrelation in the dynamic simulation of urban growth using eigenvector spatial filtering. - Xinlei Yan; Yongjiu Feng; Xiaohua Tong; Pengshuo Li; Yilun Zhou; Peiqi Wu; Huan Xie; Yanming Jin; Peng Chen 025; Shijie Liu 001; Xiong Xv; Sicong Liu 001; et al. (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms. - Yilun Zhou; Adi Renduchintala; Xian Li 003; Sida Wang 001; Yashar Mehdad; Asish Ghoshal (CoRR, 2021)

State-Visitation Fairness in Average-Reward MDPs. - Ganesh Ghalme; Vineet Nair; Vishakha Patil; Yilun Zhou (CoRR, 2021)

The Irrationality of Neural Rationale Models. - Yiming Zheng; Serena Booth; Julie Shah; Yilun Zhou (CoRR, 2021)

A comparison of proximity and accessibility drivers in simulating dynamic urban growth. - Rong Wang; Yongjiu Feng; Yongliang Wei; Xiaohua Tong; Shuting Zhai; Yilun Zhou; Peiqi Wu (Trans. GIS, 2021)

Do Feature Attribution Methods Correctly Attribute Features? - Yilun Zhou; Serena Booth; Marco Túlio Ribeiro; Julie Shah (AAAI, 2022)

Long-Term Resource Allocation Fairness in Average Markov Decision Process (AMDP) Environment. - Ganesh Ghalme; Vineet Nair; Vishakha Patil; Yilun Zhou (AAMAS, 2022)

ExSum: From Local Explanations to Model Understanding. - Yilun Zhou; Marco Túlio Ribeiro; Julie Shah (NAACL-HLT, 2022)

The effects of factor generalization scales on the reproduction of dynamic urban growth. - Yongjiu Feng; Peiqi Wu; Xiaohua Tong; Pengshuo Li; Rong Wang; Yilun Zhou; Jiafeng Wang; Jinyu Zhao (Geo spatial Inf. Sci., 2022)

Latent Space Alignment Using Adversarially Guided Self-Play. - Mycal Tucker; Yilun Zhou; Julie A. Shah (Int. J. Hum. Comput. Interact., 2022)

Automatic selection of permanent scatterers-based GCPs for refinement and reflattening in InSAR DEM generation. - Yongjiu Feng; Yilun Zhou; Yanling Chen 002; Pengshuo Li; Mengrong Xi; Xiaohua Tong (Int. J. Digit. Earth, 2022)

Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract). - Daking Rai; Yilun Zhou; Bailin Wang; Ziyu Yao 002 (AAAI, 2023)

Improving Generalization in Language Model-based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-based Techniques. - Daking Rai; Bailin Wang; Yilun Zhou; Ziyu Yao 002 (ACL (2), 2023)

Iterative Partial Fulfillment of Counterfactual Explanations: Benefits and Risks. - Yilun Zhou (AIES, 2023)

The Solvability of Interpretability Evaluation Metrics. - Yilun Zhou; Julie Shah (EACL (Findings), 2023)

Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations. - Shiyuan Huang; Siddarth Mamidanna; Shreedhar Jangam; Yilun Zhou; Leilani H. Gilpin (CoRR, 2023)

Evaluating the Utility of Model Explanations for Model Development. - Shawn Im; Jacob Andreas; Yilun Zhou (CoRR, 2023)

Techniques for Interpretability and Transparency of Black-Box Models - Yilun Zhou (2023)

CHAMP: A Competition-level Dataset for Fine-Grained Analyses of LLMs' Mathematical Reasoning Capabilities. - Yujun Mao; Yoon Kim; Yilun Zhou (ACL (Findings), 2024)

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases. - Rithesh Murthy; Liangwei Yang; Juntao Tan; Tulika Manoj Awalgaonkar; Yilun Zhou; Shelby Heinecke; Sachin Desai; Jason Wu; Ran Xu 001; Sarah Tan; Jianguo Zhang 005; Zhiwei Liu 001; et al. (CoRR, 2024)

A Practical Review of Mechanistic Interpretability for Transformer-Based Language Models. - Daking Rai; Yilun Zhou; Shi Feng; Abulhair Saparov; Ziyu Yao 002 (CoRR, 2024)

Direct Judgement Preference Optimization. - Peifeng Wang; Austin Xu; Yilun Zhou; Caiming Xiong; Shafiq Joty (CoRR, 2024)

Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responses. - Pranav Narayanan Venkit; Philippe Laban; Yilun Zhou; Yixin Mao; Chien-Sheng Wu (CoRR, 2024)

Research on scenario deduction and emergency decision-making evaluation for construction safety accidents. - Jianjun She; Zihao Guo; Zhijian Li; Shuwei Liang; Yilun Zhou (Reliab. Eng. Syst. Saf., 2024)

Search Engines in the AI Era: A Qualitative Understanding to the False Promise of Factual and Verifiable Source-Cited Responses in LLM-based Search. - Pranav Narayanan Venkit; Philippe Laban; Yilun Zhou; Yixin Mao; Chien-Sheng Wu (FAccT, 2025)

BingoGuard: LLM Content Moderation Tools with Risk Levels. - Fan Yin; Philippe Laban; Xiangyu Peng; Yilun Zhou; Yixin Mao; Vaibhav Vats; Linnea Ross; Divyansh Agarwal; Caiming Xiong; Chien-Sheng Wu (ICLR, 2025)

Shared Imagination: LLMs Hallucinate Alike. - Yilun Zhou; Caiming Xiong; Silvio Savarese; Chien-Sheng Wu (Trans. Mach. Learn. Res., 2025)

Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators. - Yilun Zhou; Austin Xu; Peifeng Wang; Caiming Xiong; Shafiq Joty (CoRR, 2025)

J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization. - Austin Xu; Yilun Zhou; Xuan-Phi Nguyen; Caiming Xiong; Shafiq Joty (CoRR, 2025)