Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning. - Sihui Luo 001; Xinchao Wang; Gongfan Fang; Yao Hu; Dapeng Tao; Mingli Song (IJCAI, 2019)

Data-Free Adversarial Distillation. - Gongfan Fang; Jie Song 011; Chengchao Shen; Xinchao Wang; Da Chen; Mingli Song (CoRR, 2019)

Adversarial Self-Supervised Data-Free Distillation for Text Classification. - Xinyin Ma; Yongliang Shen 001; Gongfan Fang; Chen Chen; Chenghao Jia; Weiming Lu 001 (EMNLP (1), 2020)

Impression Space from Deep Template Network. - Gongfan Fang; Xinchao Wang; Haofei Zhang; Jie Song 011; Mingli Song (CoRR, 2020)

Contrastive Model Invertion for Data-Free Knolwedge Distillation. - Gongfan Fang; Jie Song 011; Xinchao Wang; Chengchao Shen; Xingen Wang; Mingli Song (IJCAI, 2021)

Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data. - Gongfan Fang; Yifan Bao; Jie Song 011; Xinchao Wang; Donglin Xie; Chengchao Shen; Mingli Song (NeurIPS, 2021)

Contrastive Model Inversion for Data-Free Knowledge Distillation. - Gongfan Fang; Jie Song 011; Xinchao Wang; Chengchao Shen; Xingen Wang; Mingli Song (CoRR, 2021)

Up to 100x Faster Data-Free Knowledge Distillation. - Gongfan Fang; Kanya Mo; Xinchao Wang; Jie Song 011; Shitao Bei; Haofei Zhang; Mingli Song (AAAI, 2022)

Prompting to Distill: Boosting Data-Free Knowledge Distillation via Reinforced Prompt. - Xinyin Ma; Xinchao Wang; Gongfan Fang; Yongliang Shen 001; Weiming Lu 001 (IJCAI, 2022)

Federated Selective Aggregation for Knowledge Amalgamation. - Donglin Xie; Ruonan Yu; Gongfan Fang; Jie Song 011; Zunlei Feng; Xinchao Wang; Li Sun; Mingli Song (CoRR, 2022)

DepGraph: Towards Any Structural Pruning. - Gongfan Fang; Xinyin Ma; Mingli Song; Michael Bi Mi; Xinchao Wang (CVPR, 2023)

Structural Pruning for Diffusion Models. - Gongfan Fang; Xinyin Ma; Xinchao Wang (NeurIPS, 2023)

LLM-Pruner: On the Structural Pruning of Large Language Models. - Xinyin Ma; Gongfan Fang; Xinchao Wang (NeurIPS, 2023)

0.1% Data Makes Segment Anything Slim. - Zigeng Chen; Gongfan Fang; Xinyin Ma; Xinchao Wang (CoRR, 2023)

Knowledge Amalgamation for Object Detection With Transformers. - Haofei Zhang; Feng Mao; Mengqi Xue; Gongfan Fang; Zunlei Feng; Jie Song 011; Mingli Song (IEEE Trans. Image Process., 2023)

Deep semantic image compression via cooperative network pruning. - Sihui Luo 001; Gongfan Fang; Mingli Song (J. Vis. Commun. Image Represent., 2023)

DeepCache: Accelerating Diffusion Models for Free. - Xinyin Ma; Gongfan Fang; Xinchao Wang (CVPR, 2024)

Isomorphic Pruning for Vision Models. - Gongfan Fang; Xinyin Ma; Michael Bi Mi; Xinchao Wang (ECCV (30), 2024)

LiteFocus: Accelerated Diffusion Inference for Long Audio Synthesis. - Zhenxiong Tan; Xinyin Ma; Gongfan Fang; Xinchao Wang (INTERSPEECH, 2024)

SlimSAM: 0.1% Data Makes Segment Anything Slim. - Zigeng Chen; Gongfan Fang; Xinyin Ma; Xinchao Wang (NeurIPS, 2024)

AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising. - Zigeng Chen; Xinyin Ma; Gongfan Fang; Zhenxiong Tan; Xinchao Wang (NeurIPS, 2024)

Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising. - Gongfan Fang; Xinyin Ma; Xinchao Wang (NeurIPS, 2024)

MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models. - Gongfan Fang; Hongxu Yin; Saurav Muralidharan; Greg Heinrich; Jeff Pool; Jan Kautz; Pavlo Molchanov 001; Xinchao Wang (NeurIPS, 2024)

Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching. - Xinyin Ma; Gongfan Fang; Michael Bi Mi; Xinchao Wang (NeurIPS, 2024)

PruningBench: A Comprehensive Benchmark of Structural Pruning. - Haoling Li; Changhao Li; Mengqi Xue; Gongfan Fang; Sheng Zhou 004; Zunlei Feng; Huiqiong Wang; Yong Wang; Lechao Cheng; Mingli Song; Jie Song 011 (CoRR, 2024)

CoT-Valve: Length-Compressible Chain-of-Thought Tuning. - Xinyin Ma; Guangnian Wan; Runpeng Yu; Gongfan Fang; Xinchao Wang (ACL (1), 2025)

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient. - Zigeng Chen; Xinyin Ma; Gongfan Fang; Xinchao Wang (CVPR, 2025)

TinyFusion: Diffusion Transformers Learned Shallow. - Gongfan Fang; Kunjun Li; Xinyin Ma; Xinchao Wang (CVPR, 2025)

Diffusion Model is Effectively Its Own Teacher. - Xinyin Ma; Runpeng Yu; Songhua Liu; Gongfan Fang; Xinchao Wang (CVPR, 2025)

PointLoRA: Low-Rank Adaptation with Token Selection for Point Cloud Learning. - Song Wang; Xiaolu Liu; Lingdong Kong; Jianyun Xu; Chunyong Hu; Gongfan Fang; Wentong Li; Jianke Zhu; Xinchao Wang (CVPR, 2025)

Efficient Reasoning Models: A Survey. - Sicheng Feng; Gongfan Fang; Xinyin Ma; Xinchao Wang (CoRR, 2025)

Thinkless: LLM Learns When to Think. - Gongfan Fang; Xinyin Ma; Xinchao Wang (CoRR, 2025)

dKV-Cache: The Cache for Diffusion Language Models. - Xinyin Ma; Runpeng Yu; Gongfan Fang; Xinchao Wang (CoRR, 2025)

VeriThinker: Learning to Verify Makes Reasoning Model Efficient. - Zigeng Chen; Xinyin Ma; Gongfan Fang; Ruonan Yu; Xinchao Wang (CoRR, 2025)

PixelThink: Towards Efficient Chain-of-Pixel Reasoning. - Song Wang; Gongfan Fang; Lingdong Kong; Xiangtai Li; Jianyun Xu; Sheng Yang; Qiang Li; Jianke Zhu; Xinchao Wang (CoRR, 2025)

Diversity-Guided MLP Reduction for Efficient Large Vision Transformers. - Chengchao Shen; Hourun Zhu; Gongfan Fang; Jianxin Wang; Xinchao Wang (CoRR, 2025)

ConciseHint: Boosting Efficient Reasoning via Continuous Concise Hints during Generation. - Siao Tang; Xinyin Ma; Gongfan Fang; Xinchao Wang (CoRR, 2025)