Zhenjiang Mao

According to our database, Zhenjiang Mao authored at least 13 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Anomaly-Informed Confidence Calibration for Vision-Based Safety Prediction.

Zhenjiang Mao, Jiawen Wu, Gabriel Wagner, Zhongzheng Zhang, Ivan Ruchkin

CoRR, May, 2026

Confidence over Time: Confidence Calibration with Temporal Logic for Large Language Model Reasoning.

Zhenjiang Mao, Anirudhh Venkat, Artem Bisliouk, Akshat Kothiyal, Sindhura Kumbakonam Subramanian, Saithej Singhu, Ivan Ruchkin

CoRR, January, 2026

Recurrent Confidence Chain: Temporal-Aware Uncertainty Quantification in Large Language Models.

Zhenjiang Mao, Anirudhh Venkat

CoRR, January, 2026

2025

How Safe Will I Be Given What I Saw? Calibrated Prediction of Safety Chances for Image-Controlled Autonomy.

Zhenjiang Mao, Mrinall Eashaan Umasudhan, Ivan Ruchkin

CoRR, August, 2025

Generalizable Image Repair for Robust Visual Autonomous Racing.

Carson Sobolewski, Zhenjiang Mao, Kshitij Maruti Vejre, Ivan Ruchkin

CoRR, March, 2025

Four Principles for Physically Interpretable World Models.

Jordan Peper, Zhenjiang Mao, Yuang Geng, Siyuan Pan, Ivan Ruchkin

Proceedings of the International Conference on Neuro-symbolic Systems, 2025

Generalizable Image Repair for Robust Visual Control.

Carson Sobolewski, Zhenjiang Mao, Kshitij Maruti Vejre, Ivan Ruchkin

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

Temporalizing Confidence: Evaluation of Chain-of-Thought Reasoning with Signal Temporal Logic.

Zhenjiang Mao, Artem Bisliouk, Rohith Reddy Nama, Ivan Ruchkin

Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications, 2025

2024

Towards Physically Interpretable World Models: Meaningful Weakly Supervised Representations for Visual Trajectory Prediction.

Zhenjiang Mao, Ivan Ruchkin

CoRR, 2024

Language-Enhanced Latent Representations for Out-of-Distribution Detection in Autonomous Driving.

Zhenjiang Mao, Dong-You Jhong, Ao Wang, Ivan Ruchkin

CoRR, 2024

Zero-shot Safety Prediction for Autonomous Robots with Foundation World Models.

Zhenjiang Mao, Siqi Dai, Yuang Geng, Ivan Ruchkin

CoRR, 2024

How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy.

Zhenjiang Mao, Carson Sobolewski, Ivan Ruchkin

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

2021

A 720-mVpp 224-Gb/s PAM4 Optical Receiver with Multiple Peaking Techniques in 130-nm SiGe BiCMOS.

Qi Zhang, Xiongshi Luo, Zhenghao Li, Dongfan Xu, Siqiang Zhu, Leiming Wang, Zhenjiang Mao, Xiaoyan Gui, Dan Li, Hongyu Yu, Quan Pan

Proceedings of the IEEE Asia Pacific Conference on Circuit and Systems, 2021