Single-shot Embedding Dimension Search in Recommender System. - Liang Qu; Yonghong Ye; Ningzhi Tang; Lixin Zhang; Yuhui Shi 001; Hongzhi Yin (SIGIR, 2022)

Semi-decentralized Federated Ego Graph Learning for Recommendation. - Liang Qu; Ningzhi Tang; Ruiqi Zheng; Quoc Viet Hung Nguyen; Zi Huang; Yuhui Shi 001; Hongzhi Yin (WWW, 2023)

CodeGRITS: A Research Toolkit for Developer Behavior and Eye Tracking in IDE. - Ningzhi Tang; Junwen An; Meng Chen; Aakash Bansal; Yu Huang 015; Collin McMillan; Toby Jia-Jun Li (ICSE Companion, 2024)

Towards Effective Validation and Integration of LLM-Generated Code. - Ningzhi Tang (VL/HCC, 2024)

Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking. - Ningzhi Tang; Meng Chen; Zheng Ning; Aakash Bansal; Yu Huang 015; Collin McMillan; Toby Jia-Jun Li (VL/HCC, 2024)

A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions. - Ningzhi Tang; Meng Chen; Zheng Ning; Aakash Bansal; Yu Huang 015; Collin McMillan; Toby Jia-Jun Li (CoRR, 2024)

Enabling On-Device Learning via Experience Replay with Efficient Dataset Condensation. - Gelei Xu; Ningzhi Tang; Jun Xia 003; Wei Jin 009; Yiyu Shi 001 (CoRR, 2024)

Enabling Memory-Efficient On-Device Learning via Dataset Condensation. - Gelei Xu; Ningzhi Tang; Jun Xia 003; Ruiyang Qin; Wei Jin 009; Yiyu Shi 001 (DATE, 2025)

Programmer Visual Attention During Context-Aware Code Summarization. - Robert Wallace; Aakash Bansal; Zachary Karas; Ningzhi Tang; Yu Huang 015; Toby Jia-Jun Li; Collin McMillan (IEEE Trans. Software Eng., 2025)

Exploring Direct Instruction and Summary-Mediated Prompting in LLM-Assisted Code Modification. - Ningzhi Tang; Emory Smith; Yu Huang 015; Collin McMillan; Toby Jia-Jun Li (CoRR, 2025)