Jiawei Zhou

According to our database, Jiawei Zhou authored at least 10 papers between 2017 and 2026.

Collaborative distances:

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

2026

Lost in Instructions: Study of Blind Users' Experiences with DIY Manuals and AI-Rewritten Instructions for Assembly, Operation, and Troubleshooting of Tangible Products.

Monalika Padma Reddy, Aruna Balasubramanian, Jiawei Zhou, Xiaojun Bi, I. V. Ramakrishnan, Vikas Ashok

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, 2026

Finding the Signal in the Noise: An Exploratory Study on Assessing the Effectiveness of AI and Accessibility Forums for Blind Users' Support Needs.

Satwik Ram Kodandaram, Jiawei Zhou, Xiaojun Bi, I. V. Ramakrishnan, Vikas Ashok

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, 2026

2025

An Outlook on the Opportunities and Challenges of Multi-Agent AI Systems.

Fangqiao Tian, An Luo, Jin Du, Xun Xian, Robert Specht, Ganghua Wang, Xuan Bi, Jiawei Zhou, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Rui Zhang, Zirui Liu, Mingyi Hong, Jie Ding

CoRR, May, 2025

Intent-Driven Network Management with Multi-Agent LLMs: The Confucius Framework.

Zhaodong Wang, Samuel Lin, Guanqing Yan, Soudeh Ghorbani, Minlan Yu, Jiawei Zhou, Nathan Hu, Lopa Baruah, Sam Peters, Srikanth Kamath, Jerry Yang, Ying Zhang

Proceedings of the ACM SIGCOMM 2025 Conference, 2025

Beyond Expectations: Quantile-Guided Alignment for Risk-Calibrated Language Models.

Xinran Wang, Jin Du, Azal Ahmad Khan, Qi Le, Enmao Diao, Jiawei Zhou, Jie Ding, Ali Anwar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science.

An Luo, Xun Xian, Jin Du, Fangqiao Tian, Ganghua Wang, Ming Zhong, Shengchun Zhao, Xuan Bi, Zirui Liu, Jiawei Zhou, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2021

On Statistical Efficiency in Learning.

Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh

IEEE Trans. Inf. Theory, 2021

2019

Asymptotically Optimal Prediction for Time-Varying Data Generating Processes.

Jie Ding, Jiawei Zhou, Vahid Tarokh

IEEE Trans. Inf. Theory, 2019

2018

A Penalized Method for the Predictive Limit of Learning.

Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Optimal prediction of data with unknown abrupt change points.

Jie Ding, Jiawei Zhou, Vahid Tarokh

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