Multi-label Learning by Exploiting Imbalanced Label Correlations. - Shiqiao Gu; Liu Yang; Yaning Li; Hui Li 069 (PRICAI (2), 2021)

Two-Stream Communication-Efficient Federated Pruning Network. - Shiqiao Gu; Liu Yang; Siqi Deng; Zhengyi Xu (PRICAI (3), 2022)

Heterogeneous Federated Learning Based on Graph Hypernetwork. - Zhengyi Xu; Liu Yang; Shiqiao Gu (ICANN (3), 2023)

Skeleton Neural Networks via Low-Rank Guided Filter Pruning. - Liu Yang; Shiqiao Gu; Chenyang Shen; Xile Zhao; Qinghua Hu (IEEE Trans. Circuits Syst. Video Technol., 2023)

LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit. - Ruihao Gong; Yang Yong; Shiqiao Gu; Yushi Huang; Chengtao Lv; Yunchen Zhang; Dacheng Tao; Xianglong Liu 001 (EMNLP (Industry Track), 2024)

LLM-QBench: A Benchmark Towards the Best Practice for Post-training Quantization of Large Language Models. - Ruihao Gong; Yang Yong; Shiqiao Gu; Yushi Huang; Yunchen Zhang; Xianglong Liu 001; Dacheng Tao (CoRR, 2024)

Soft independence guided filter pruning. - Liu Yang; Shiqiao Gu; Chenyang Shen; Xile Zhao; Qinghua Hu (Pattern Recognit., 2024)

LLMC+: Benchmarking Vision-Language Model Compression with a Plug-and-play Toolkit. - Chengtao Lv; Bilang Zhang; Yang Yong; Ruihao Gong; Yushi Huang; Shiqiao Gu; Jiajun Wu 004; Yumeng Shi; Jinyang Guo; Wenya Wang (CoRR, 2025)