Yu Mao

According to our database, Yu Mao authored at least 21 papers between 2021 and 2025.

Collaborative distances:

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

2025

Lossless Compression of Large Language Model-Generated Text via Next-Token Prediction.

Yu Mao, Holger Pirk, Chun Jason Xue

CoRR, May, 2025

Accelerating point cloud analytics on resource-constrained edge devices.

Jingzong Li, Yik Hong Cai, Libin Liu, Yu Mao, Chun Jason Xue, Hong Xu

Comput. Networks, 2025

DAWN: Accelerating Point Cloud Object Detection via Object-Aware Partitioning and 3D Similarity-Based Filtering.

Dongdong Tang, Yu Mao, Weilan Wang, Nan Guan, Tei-Wei Kuo, Chun Jason Xue

Proceedings of the 62nd ACM/IEEE Design Automation Conference, 2025

Easz: An Agile Transformer-based Image Compression Framework for Resource-constrained IoTs.

Yu Mao, Jingzong Li, Jun Wang, Hong Xu, Tei-Wei Kuo, Nan Guan, Chun Jason Xue

Proceedings of the 62nd ACM/IEEE Design Automation Conference, 2025

WISE: A Framework for Gigapixel Whole-Slide-Image Lossless Compression.

Yu Mao, Jun Wang, Nan Guan, Chun Jason Xue

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

SHAP-CAT: A interpretable multi-modal framework enhancing WSI classification via virtual staining and shapley-value-based multimodal fusion.

Jun Wang, Yu Mao, Nan Guan, Chun Jason Xue

CoRR, 2024

Advances in Multiple Instance Learning for Whole Slide Image Analysis: Techniques, Challenges, and Future Directions.

Jun Wang, Yu Mao, Nan Guan, Chun Jason Xue

CoRR, 2024

IHC Matters: Incorporating IHC analysis to H&E Whole Slide Image Analysis for Improved Cancer Grading via Two-stage Multimodal Bilinear Pooling Fusion.

Jun Wang, Yu Mao, Yufei Cui, Nan Guan, Chun Jason Xue

CoRR, 2024

Pre-processing matters: A segment search method for WSI classification.

Jun Wang, Yufei Cui, Yu Mao, Nan Guan, Chun Jason Xue

CoRR, 2024

On the Compressibility of Quantized Large Language Models.

Yu Mao, Weilan Wang, Hongchao Du, Nan Guan, Chun Jason Xue

CoRR, 2024

STEM: Streaming-Based FPGA Acceleration for Large-Scale Compactions in LSM KV.

Dongdong Tang, Weilan Wang, Yu Mao, Jinghuan Yu, Tei-Wei Kuo, Chun Jason Xue

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

When Compression Meets Model Compression: Memory-Efficient Double Compression for Large Language Models.

Weilan Wang, Yu Mao, Dongdong Tang, Hongchao Du, Nan Guan, Chun Jason Xue

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Variational Nested Dropout.

Yufei Cui, Yu Mao, Ziquan Liu, Qiao Li, Antoni B. Chan, Xue (Steve) Liu, Tei-Wei Kuo, Chun Jason Xue

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

2D-Empowered 3D Object Detection on the Edge.

Jingzong Li, Yik Hong Cai, Libin Liu, Yu Mao, Chun Jason Xue, Hong Xu

CoRR, 2023

Moby: Empowering 2D Models for Efficient Point Cloud Analytics on the Edge.

Jingzong Li, Yik Hong Cai, Libin Liu, Yu Mao, Chun Jason Xue, Hong Xu

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

Faster and Stronger Lossless Compression with Optimized Autoregressive Framework.

Yu Mao, Jingzong Li, Yufei Cui, Chun Jason Xue

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

A Fast Transformer-based General-Purpose Lossless Compressor.

Yu Mao, Yufei Cui, Tei-Wei Kuo, Chun Jason Xue

CoRR, 2022

TRACE: A Fast Transformer-based General-Purpose Lossless Compressor.

Yu Mao, Yufei Cui, Tei-Wei Kuo, Chun Jason Xue

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Accelerating General-purpose Lossless Compression via Simple and Scalable Parameterization.

Yu Mao, Yufei Cui, Tei-Wei Kuo, Chun Jason Xue

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

2021

The Implicit Biases of Stochastic Gradient Descent on Deep Neural Networks with Batch Normalization.

Ziquan Liu, Yufei Cui, Jia Wan, Yu Mao, Antoni B. Chan

CoRR, 2021

Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression.

Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue

CoRR, 2021