Fangmin Chen

According to our database, Fangmin Chen authored at least 12 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

TAP: A Token-Adaptive Predictor Framework for Training-Free Diffusion Acceleration.

Haowei Zhu, Tingxuan Huang, Xing Wang, Tianyu Zhao, Jiexi Wang, Weifeng Chen, Xurui Peng, Fangmin Chen, Junhai Yong, Bin Wang

CoRR, March, 2026

S2O: Early Stopping for Sparse Attention via Online Permutation.

Yu Zhang, Songwei Liu, Chenqian Yan, Sheng Lin, Beichen Ning, Fangmin Chen, Xing Wang

CoRR, February, 2026

Train Short, Inference Long: Training-free Horizon Extension for Autoregressive Video Generation.

Jia Li, Xiaomeng Fu, Xurui Peng, Weifeng Chen, Youwei Zheng, Tianyu Zhao, Jiexi Wang, Fangmin Chen, Xing Wang, Hayden Kwok-Hay So

CoRR, February, 2026

NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation.

Huichao Zhang, Liao Qu, Yiheng Liu, Hang Chen, Yangyang Song, Yongsheng Dong, Shikun Sun, Xian Li, Xu Wang, Yi Jiang, Hu Ye, Bo Chen, Yiming Gao, Peng Liu, Akide Liu, Zhipeng Yang, Qili Deng, Linjie Xing, Jiyang Liu, Zhao Wang, Yang Zhou, Mingcong Liu, Yi Zhang, Qian He, Xiwei Hu, Zhongqi Qi, Jie Shao, Zhiye Fu, Shuai Wang, Fangmin Chen, Xuezhi Chai, Zhihua Wu, Yitong Wang, Zehuan Yuan, Daniel K. Du, Xinglong Wu

CoRR, January, 2026

2025

ERTACache: Error Rectification and Timesteps Adjustment for Efficient Diffusion.

Xurui Peng, Hong Liu, Chenqian Yan, Rui Ma, Fangmin Chen, Xing Wang, Zhihua Wu, Songwei Liu, Mingbao Lin

CoRR, August, 2025

Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion.

Songwei Liu, Hong Liu, Fangmin Chen, Xurui Peng, Chenqian Yan, Lean Fu, Xing Mei

CoRR, August, 2025

GQSA: Group Quantization and Sparsity for Accelerating Large Language Model Inference.

Chao Zeng, Songwei Liu, Shu Yang, Fangmin Chen, Xing Mei, Lean Fu

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

ABQ-LLM: Arbitrary-Bit Quantized Inference Acceleration for Large Language Models.

Chao Zeng, Songwei Liu, Yusheng Xie, Hong Liu, Xiaojian Wang, Miao Wei, Shu Yang, Fangmin Chen, Xing Mei

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

FoldGPT: Simple and Effective Large Language Model Compression Scheme.

Songwei Liu, Chao Zeng, Lianqiang Li, Chenqian Yan, Lean Fu, Xing Mei, Fangmin Chen

CoRR, 2024

2023

SparseByteNN: A Novel Mobile Inference Acceleration Framework Based on Fine-Grained Group Sparsity.

Haitao Xu, Songwei Liu, Yuyang Xu, Shuai Wang, Jiashi Li, Chenqian Yan, Liangqiang Li, Lean Fu, Xin Pan, Fangmin Chen

CoRR, 2023

Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution.

Yong Liu, Hang Dong, Boyang Liang, Songwei Liu, Qingji Dong, Kai Chen, Fangmin Chen, Lean Fu, Fei Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

2022

Residual Local Feature Network for Efficient Super-Resolution.

Fangyuan Kong, Mingxi Li, Songwei Liu, Ding Liu, Jingwen He, Yang Bai, Fangmin Chen, Lean Fu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022