Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability. - Michael Tsang; Hanpeng Liu; Sanjay Purushotham; Pavankumar Murali; Yan Liu 002 (NeurIPS, 2018)

Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks. - Shangxing Wang; Hanpeng Liu; Pedro Henrique Gomes; Bhaskar Krishnamachari (IEEE Trans. Cogn. Commun. Netw., 2018)

CoSTCo: A Neural Tensor Completion Model for Sparse Tensors. - Hanpeng Liu; Yaguang Li; Michael Tsang; Yan Liu 002 (KDD, 2019)

Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions. - Weiran Shen; Binghui Peng; Hanpeng Liu; Michael Zhang; Ruohan Qian; Yan Hong; Zhi Guo; Zongyao Ding; Pengjun Lu; Pingzhong Tang (AAAI, 2020)

Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. - Michael Tsang; Dehua Cheng; Hanpeng Liu; Xue Feng; Eric Zhou; Yan Liu 002 (ICLR, 2020)

Class-aware Information for Logit-based Knowledge Distillation. - Shuoxi Zhang; Hanpeng Liu; John E. Hopcroft; Kun He 001 (CoRR, 2022)

Knowledge Distillation via Token-level Relationship Graph. - Shuoxi Zhang; Hanpeng Liu; Kun He 001 (CoRR, 2023)

You Only Need Less Attention at Each Stage in Vision Transformers. - Shuoxi Zhang; Hanpeng Liu; Stephen Lin 001; Kun He 001 (CVPR, 2024)

Grouped Logit Distillation Enhanced with Superclass Awareness for Efficient Knowledge Transfer. - Shuoxi Zhang; Hanpeng Liu; Yuyi Wang 001; Kun He 001 (ECAI, 2024)

Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers. - Jinsong Chen 002; Hanpeng Liu; John E. Hopcroft; Kun He 001 (NeurIPS, 2024)

Knowledge Distillation via Token-Level Relationship Graph Based on the Big Data Technologies. - Shuoxi Zhang; Hanpeng Liu; Kun He 001 (Big Data Res., 2024)

Class Discriminative Knowledge Distillation. - Shuoxi Zhang; Hanpeng Liu; Yuyi Wang 001; Kun He 001; Jun Lin 005; Yang Zeng (IEEE Trans. Emerg. Top. Comput. Intell., 2025)