From Beginner to Master: A Survey for Deep Learning-based Single-Image Super-Resolution. - Juncheng Li 003; Zehua Pei; Tieyong Zeng (CoRR, 2021)

Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields. - Guojin Chen; Zehua Pei; Haoyu Yang; Yuzhe Ma; Bei Yu 001; Martin D. F. Wong (DAC, 2023)

AlphaSyn: Logic Synthesis Optimization with Efficient Monte Carlo Tree Search. - Zehua Pei; Fangzhou Liu; Zhuolun He; Guojin Chen; Haisheng Zheng; Keren Zhu 001; Bei Yu 001 (ICCAD, 2023)

LSTP: A Logic Synthesis Timing Predictor. - Haisheng Zheng; Zhuolun He; Fangzhou Liu; Zehua Pei; Bei Yu 001 (ASPDAC, 2024)

CBTune: Contextual Bandit Tuning for Logic Synthesis. - Fangzhou Liu; Zehua Pei; Ziyang Yu 001; Haisheng Zheng; Zhuolun He; Tinghuan Chen; Bei Yu 001 (DATE, 2024)

BetterV: Controlled Verilog Generation with Discriminative Guidance. - Zehua Pei; Hui-Ling Zhen; Mingxuan Yuan; Yu Huang 005; Bei Yu 001 (ICML, 2024)

SoLA: Solver-Layer Adaption of LLM for Better Logic Reasoning. - Yu Zhang 189; Hui-Ling Zhen; Zehua Pei; Yingzhao Lian; Lihao Yin; Mingxuan Yuan; Bei Yu 001 (CoRR, 2024)

FuseGPT: Learnable Layers Fusion of Generative Pre-trained Transformers. - Zehua Pei; Hui-Ling Zhen; Xianzhi Yu; Sinno Jialin Pan; Mingxuan Yuan; Bei Yu 001 (CoRR, 2024)

A Systematic Survey of Deep Learning-Based Single-Image Super-Resolution. - Juncheng Li 003; Zehua Pei; Wenjie Li; Guangwei Gao; Longguang Wang; Yingqian Wang 002; Tieyong Zeng (ACM Comput. Surv., 2024)

Quantization via Distillation and Contrastive Learning. - Zehua Pei; Xufeng Yao; Wenqian Zhao; Bei Yu 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference. - Zehua Pei; Lancheng Zou; Hui-Ling Zhen; Xianzhi Yu; Wulong Liu; Sinno Jialin Pan; Mingxuan Yuan; Bei Yu 001 (CoRR, 2025)

PreMoe: Lightening MoEs on Constrained Memory by Expert Pruning and Retrieval. - Zehua Pei; Yingchun Zhang; Hui-Ling Zhen; Xianzhi Yu; Wulong Liu; Sinno Jialin Pan; Mingxuan Yuan; Bei Yu 001 (CoRR, 2025)