Automated Quantization Range Mapping for DAC/ADC Non-linearity in Computing-In-Memory. - Chi-Tse Huang; Yu-Chuan Chuang; Ming-Guang Lin; An-Yeu Andy Wu (ISCAS, 2022)

D-NAT: Data-Driven Non-Ideality Aware Training Framework for Fabricated Computing-In-Memory Macros. - Ming-Guang Lin; Chi-Tse Huang; Yu-Chuan Chuang; Yi-Ta Chen; Ying-Tuan Hsu; Yu-Kai Chen; Jyun-Jhe Chou; Tsung-Te Liu; Chi-Sheng Shih 001; An-Yeu Wu (IEEE J. Emerg. Sel. Topics Circuits Syst., 2022)

TSPTQ-ViT: Two-Scaled Post-Training Quantization for Vision Transformer. - Yu-Shan Tai; Ming-Guang Lin; An-Yeu Andy Wu (ICASSP, 2023)

Approximate Adder Tree Design with Sparsity-Aware Encoding and In-Memory Swapping for SRAM-based Digital Compute-In-Memory Macros. - Ming-Guang Lin; Jiing-Ping Wang; Cheng-Yang Chang; An-Yeu Andy Wu (AICAS, 2024)

LATTE: Low-Precision Approximate Attention with Head-wise Trainable Threshold for Efficient Transformer. - Jiing-Ping Wang; Ming-Guang Lin; An-Yeu Andy Wu (AICAS, 2024)

A 28nm 64.5TOPS/W Sparse Transformer Accelerator with Partial Product-based Speculation and Sparsity-Adaptive Computation. - Ming-Guang Lin; Jiing-Ping Wang; Yuan-June Luo; An-Yeu Andy Wu (APCCAS, 2024)

A 40nm 24.6TOPS/W Scalable EfficientDet Processor for Object Detection. - Yu-Chuan Chuang; Ming-Guang Lin; Chi-Tse Huang; Chieh-Fang Teng; Cheng-Yang Chang; Yi-Ta Chen; An-Yeu Andy Wu (ISCAS, 2024)

Similarity-Aware Fast Low-Rank Decomposition Framework for Vision Transformers. - Yuan-June Luo; Yu-Shan Tai; Ming-Guang Lin; An-Yeu Andy Wu (ISCAS, 2024)

Retraining-free Constraint-aware Token Pruning for Vision Transformer on Edge Devices. - Yun-Chia Yu; Mao-Chi Weng; Ming-Guang Lin; An-Yeu Andy Wu (ISCAS, 2024)

WS-CIM: Enabling Fast and Simultaneous Update for Multi-Macro Compute-in-Memory Architecture Using Weight Sharing Technique. - Yan-Ding Shieh; Ming-Guang Lin; Hung-Yu Wang; An-Yeu Andy Wu (ISCAS, 2025)