FedTiny: Pruned Federated Learning Towards Specialized Tiny Models. - Hong Huang 005; Lan Zhang 005; Chaoyue Sun; Ruogu Fang; Xiaoyong Yuan; Dapeng Wu 001 (CoRR, 2022)

Distributed Pruning Towards Tiny Neural Networks in Federated Learning. - Hong Huang 005; Lan Zhang 005; Chaoyue Sun; Ruogu Fang; Xiaoyong Yuan; Dapeng Wu 001 (ICDCS, 2023)

FedMef: Towards Memory-Efficient Federated Dynamic Pruning. - Hong Huang 005; Weiming Zhuang; Chen Chen 043; Lingjuan Lyu (CVPR, 2024)

Texture and motion aware perception in-loop filter for AV1. - Tianqi Liu; Hong Huang 005; Zhijun Lei; Ruogu Fang; Dapeng Oliver Wu (J. Vis. Commun. Image Represent., 2024)

Quaff: Quantized Parameter-Efficient Fine-Tuning under Outlier Spatial Stability Hypothesis. - Hong Huang 005; Dapeng Wu 001 (ACL (1), 2025)

FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling. - Hong Huang 005; Jinhai Yang 006; Yuan Chen; Jiaxun Ye; Dapeng Wu 001 (NeurIPS, 2025)

FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling. - Hong Huang 005; Hai Yang; Yuan Chen; Jiaxun Ye; Dapeng Oliver Wu (CoRR, 2025)

Tequila: Trapping-free Ternary Quantization for Large Language Models. - Hong Huang 005; Decheng Wu; Rui Cen; Guanghua Yu; Zonghang Li; Kai Liu 052; Jianchen Zhu; Peng Chen 021; Xue Liu; Dapeng Wu 001 (CoRR, 2025)

AquaFed: Ascending Quantized Federated Learning on Heterogeneous Devices. - Juntao Hu; Hong Huang 005; Kuan Liu; Huimin Lu; Bingyi Liu; Dapeng Wu 001 (IEEE Trans. Cloud Comput., 2026)

Sherry: Hardware-Efficient 1.25-Bit Ternary Quantization via Fine-grained Sparsification. - Hong Huang 005; Decheng Wu; Qiangqiang Hu; Guanghua Yu; Jinhai Yang 006; Jianchen Zhu; Xue Liu; Dapeng Wu 001 (CoRR, 2026)

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk? - Hongyu Li; Kuan Liu; Yuan Chen; Juntao Hu; Huimin Lu; Guanjie Chen; Xue Liu; Guangming Lu; Hong Huang 005 (CoRR, 2026)