Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning. - Hande Dong; Zhaolin Ding; Xiangnan He 001; Fuli Feng; Shuxian Bi (CoRR, 2020)

AutoDebias: Learning to Debias for Recommendation. - Jiawei Chen 007; Hande Dong; Yang Qiu; Xiangnan He 001; Xin Xin 003; Liang Chen 001; Guli Lin; Keping Yang (SIGIR, 2021)

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation. - Hande Dong; Jiawei Chen 007; Fuli Feng; Xiangnan He 001; Shuxian Bi; Zhaolin Ding; Peng Cui 001 (WWW, 2021)

Retriever and Ranker Framework with Probabilistic Hard Negative Sampling for Code Search. - Hande Dong; Jiayi Lin 004; Yichong Leng; Jiawei Chen; Yutao Xie (CoRR, 2023)

A Survey of Deep Code Search. - Yutao Xie; Jiayi Lin 004; Hande Dong; Lei Zhang 001; Zhonghai Wu (CoRR, 2023)

Bias and Debias in Recommender System: A Survey and Future Directions. - Jiawei Chen 007; Hande Dong; Xiang Wang 010; Fuli Feng; Meng Wang 001; Xiangnan He 001 (ACM Trans. Inf. Syst., 2023)

Improving Code Search with Hard Negative Sampling Based on Fine-tuning. - Hande Dong; Jiayi Lin 004; Yanlin Wang; Yichong Leng; Jiawei Chen; Yutao Xie (APSEC, 2024)

Scaling Laws Behind Code Understanding Model. - Jiayi Lin 004; Hande Dong; Yutao Xie; Lei Zhang 001 (CoRR, 2024)

Survey of Code Search Based on Deep Learning. - Yutao Xie; Jiayi Lin 004; Hande Dong; Lei Zhang 001; Zhonghai Wu (ACM Trans. Softw. Eng. Methodol., 2024)

EFIM: Efficient Serving of LLMs for Infilling Tasks with Improved KV Cache Reuse. - Tianyu Guo 009; Hande Dong; Yichong Leng; Feng Liu; Cheater Lin; Nong Xiao 001; Xianwei Zhang 001 (Euro-Par (2), 2025)

ReDit: Reward Dithering for Improved LLM Policy Optimization. - Chenxing Wei; Jiarui Yu; Ying Tiffany He; Hande Dong; Yao Shu; Fei Yu (CoRR, 2025)

UniSVG: A Unified Dataset for Vector Graphic Understanding and Generation with Multimodal Large Language Models. - Jinke Li; Jiarui Yu; Chenxing Wei; Hande Dong; Qiang Lin; Liangjing Yang; Zhicai Wang; Yanbin Hao (CoRR, 2025)